Database Management System And Information Retrieval...

Database Management System And Information Retrieval...
Differentiate between database management system and information retrieval system by focusing on
their functionalities. A database management system in the main software tool of the database
management approach because it controls the creation, maintenance, and use of the database of an
organization and its users. The three major functions of a database management system are first to
create new database and database application. Second to maintain the quality of the data in an
organized database. And last to use the database of an organization to provide the information that
its end users need. An example of a database management approach in a banking information
system. Note how the savings, checking and installment loan programs use a ... Show more content
on Helpwriting.net ...
Highlight the differences between data and information. The difference between data and
information. Data usually is a form of attachment figures are relative. From a data will be processed
into a information important for the owners. Usually treatment of an information to be able to give
us an information in written and oral form.
Information may be derived from which only. We can see from the difference source of information
available. But we should be able to see how a data that has been processed into an information
would be helpful to be able making an important decision.
We can try looking from the side of the data can be processed as a valid information. This
information will later be able to be one of the key components of the side of a system. We can see
from the side of various systems (SIM) and Decision Support System (DSS), a system based on
knowledge (knowledge–based system).
From some of the system will be able to form a network of information system using a computer or
commonly called the CBIS (Computer Based Information System). From an information system is
then we will get to see some professional employees will be needed in this area, namely as
... Get more on HelpWriting.net ...

How Far Does Google Limit Aucians ' Perception Of The...
Annotated Bibliography Research Question: How Far does Google limit AUCians' perception of the
universe? o Are AUCians aware of such monitoring and tracking? o Are AUCians aware that they
are given the part of the information relative to their own point of view? 1) Source One: (Primary)
Pan, B., Hembrooke, H., Joachims, T., Lorigo, L., Gay, G., & Granka, L. (2007, April). In google we
trust: Users' decisions on rank, position, and relevance. Journal of Computer–Mediated
Communication, Vol. 12, No. 3, 801–823. doi:10.1111/j.1083–6101.2007.00351
(http://onlinelibrary.wiley.com.libproxy.aucegypt.edu:2048/doi/10.1111/j.1083–
6101.2007.00351.x/full) This study by Pan, Hembrooke, Joachims, Lorigo, Gay & Granka was done
to evaluate college students' trust in Google's capability to rank results by their spot–on applicability
to the search inquiry. This study was carried out on 22 undergraduate students around the age of 20
who claimed they used Google as their main search engine. The students had to calibrate eye
trackers so that the researchers would be able to monitor their eye movements regarding the search
results. Search results were slightly modified to manipulate their order so as to see the response of
the students towards that. The results indicated that students chose the result that was higher in
position even if the abstract was unrelated. These findings are rather relevant to the study as it shows
how students have great trust in Google's search algorithms. 2) Source

Googlization
Abstract
In this paper, the main focus will lie on the differences that the librarians and students have when
they tend to retrieve or manage the information that they search through online databases.
Furthermore, we will discuss the importance of the knowledge management and controlled
vocabulary as the main distinction between those librarians who are successful at information
retrieval and teaching it and those students that aren't. We will discuss this under the light of some of
the large search engines or web portals that are available to the librarians and the students as part of
their search archives like Google; highlighting some of the facts that should be known and/or taught
about these web portals before they can be used to ... Show more content on Helpwriting.net ...
Furthermore, comparisons of librarians and students showed that the overall advantage of the
accurate collection and retention of data was with the librarians because of the methodologies that
they used top collect the information. The question then remains whether these librarians can
efficiently and effectively teach these students the techniques that they use to gather information and
allow them to exercise the same skills of knowledge management and controlled use of vocabulary
and words within and outside the environment of the libraries (Gadzella and Baloglu, 2003).
There are many academic psychologists and practitioners who have focused on this difference of
success between the librarians and the students when it comes to understanding, retracting,
managing and using the data that they gather fore a topic. Some researches chose to focus on the
behaviors, characteristics, mental abilities and overall skill sets of the two entities to analyze the
foundation behind the differences. There is a generalized belief among the researchers that the
differences between the success of librarians and students does lie in the overall approach to the
retrieval of information and the foundation, mental and personal, behind that approach. Furthermore,
many researchers believe that the ability to retain the facts is also highly dependent upon the value
or worth associated with them search (Gadzella and Baloglu, 2003).
Information Search and Collection
The fact of the

Web Search For Web Searching Engine Essay
Abstract–Web searching engine are mostly used for finding certain information among a huge
amount of data in a minimum amount of period. Profile based personalized web search (PWS) has
determine their effectiveness in improving the quality of various internet search technique. We study
security of privacy protection for PWS applications that as hierarchical user profiles. In this paper
we can implement the PWS system called UPS that can flexibly create profiles by queries while
regarding user definite privacy requirements. Our runtime generalization goals at striking a level
between two predictive metrics that evaluate the effectiveness of personalization and the privacy
risk of exposing the generalized profile. We implemented this system with greedy algorithms, for
runtime profile generalization also provides a runtime prediction mechanism for determining
whether personalizing a query is useful. Extensive experiments prove the effectiveness of our
system. The experimental results also reveal that Greedy algorithms significantly outperform in
terms of effectiveness. Index Terms–Profile, Personalized web search, Greedy algorithms, Privacy
protection, Risk , Security. F 1 INTRODUCTION WEB searching engine are most important portal
for people who are looking for some useful information related to their re– quirement from the web.
When search engine return some unwanted result then that may be failure for the user search and do
not meet real meanings. This irrelevance

State of the Art in Multilingual Text Retrieval Accessing...
In this paper we surveyed the state of the art in multilingual text retrieval accessing parallel web
pages. Multilingual search engines typically consist of a crawler which traverses the web, retrieves
the required web page in the desire languages. It provides front end user interface, which can be
used for selecting language for query submission. The way the query is fired leads into two types of
search Cross–language information retrieval and Multi–language information retrieval. In cross–
language retrieval the user query is machine translated into multiple language queries automatically
as per user selection and then fired. In multi–language retrieval the user has to provide queries in
multiple languages to fetch the web documents in different languages. Also in some search engine
the web page is machine translated and forwarded to the user. NLP is still in the expansion phase
and has to make advances in it, research is going on all over world. Experiment was done with top
rated multilingual search engine to access parallel pages but could not find it. When billions of
parallel web documents are present on the web in different languages why not explore that? A
alternative to that can be searching through parallel pair finder.
Keywords: NLP,MT Machine Translation, CLIR Cross–language, information retrieval,
Multilingual.
1. Introduction
The total number of languages in the world is between 5,000 and 10,000. In a country like India
people speak about 57 different

Example Of Annotated Bibliography
Definition of an Annotated Bibliography
Annotated Bibliography is a technique which is useful with citation. Citation information (written in
an accepted citation style, such as MLA or APA) is acceptable style of writing, with the help of these
citation we can defined Annotated Bibliography. In simple term, collecting of information /entry of
all such citation on a particular specific topic
As we all know that requirement of all person may differ, in the similar way usage of this technique
will also be different. In very simple term a bibliography that includes brief explanations or notes for
each reference, Even the requirement and usage of Bibliography differ based on the situation.
Understanding the annotated Bibliography is also important for all researcher. Some writers use an
annotated bibliography to keep track of their reading as they conduct research. Annotated
bibliographies are often created by one researcher for other researchers, in an attempt to offer a
single resource that aggregates many sources on the same topic©.
Information retrieval (IR) system is a task, ... Show more content on Helpwriting.net ...
Interpretive approach define the framework that why the evaluation is is being done? What is being
evaluated? Who affects the evaluation? When is the evaluation taking place? And how is the
evaluation to be carried out?. Study were performed on 22 users by using eclectic approach which
means selecting of individual element from variety of sources. Output of the study demonstrate huge
variation among all cases, evaluation result were different within same case. The final conclusion
was that those who are participating in evaluation should be well aware of the difficulties. User
should have good understanding of the concept and question.
C] Onwuchekwa, Edeama O. and Jegede, Olumakinde Richard (2011) "Information Retrieval
Methods in Libraries and Information

Using The Library Search Tools And 1-2 Multimedia Resources
A. Individually, find 3 sources: 1–2 scholarly articles using the library search tools and 1–2
multimedia resources (TED talks, Youtube videos, etc) about the Global Issue your team has
selected.
B. List them in alphabetical order using correct MLA or APA citation format.
C. After each citation, please apply the CRAAP test to help determine if this is reliable information.
D. For each of these three, after the CRAAP application, please write a 100–word summary in
which you explain how you found it (include search terms and database), why you think it's worth
sharing with your teammates, and what facet of your Global issue it illuminates. E. Post the
Individual Summaries & Citations as a document to the Assignment link above (just click on the
underlined title of the assignment)
Topic and questions
1. What is the response from communities in the U.S. to the Syrian refugee crisis, and how can this
response be improved?
2. The cohesion and peace within communities, along with the economic and social stability; the
lives of the refugees.
3. Definitions:
a. Cultural relativism is looking at beliefs and values of a culture from the view point of the culture
itself.
b. Subjective relativism is the view that if a person thinks something is morally right or wrong, then
it is.
c. Emotivism says that if someone believes something is right or wrong, that doesn't make it so.
Their beliefs are based on emotions.
d. These play a role in the refugee issues

Data Mining And Multimedia Data
ABSTRACT
Data mining is a popular technology for extracting interesting information for multimedia data sets,
such as audio, video, images, graphics, speech, text and combination of several types of data set.
Multimedia data are unstructured data or semi–structured data. These data are stored in multimedia
database, multimedia mining which is used to find information from large multimedia database
system, using multimedia techniques and powerful tools. This paper analyzes about the use of
essential characteristics of multimedia data mining, retrieving information is one of the goals of data
mining and different issues have been discussed. The current approaches and techniques are
explained for mining multimedia data. In this paper applications and models of multimedia mining
are discussed clearly. Nowadays Multimedia mining has become popular field in research area.
Keywords: Data Mining, Multimedia Mining, Clustering, Classification.
1. INTRODUCTION
1.1 Multimedia data mining: Multimedia data mining is used for extracting interesting information
for multimedia data sets, such as audio, video, images, graphics, speech, text and combination of
several types of data set. Fig.1 explains about multimedia mining it is a subfield of data mining
which is used to find interesting information of implicit knowledge. Multimedia data are classified
into five types, there are (i) text data (ii) image data (iii) audio data (iv)video data and (v) electronic
and digital ink [2]. Text data

Introduction Of Cloud Storage System
CHAPTER 1 INTRODUCTION Cloud storage system is a service model in which data are
managed , maintained, and backuped remotely on the cloud side, and simultaneously keeps data
available to the users over a network. Mobile Cloud Storage (MCS) [1], [2] represents a family of
increasingly popular on–line services, and even is used as primary file storage for the mobile
devices [3]. MCS helps the mobile device users to store and retrieve files or data on the cloud
through wireless communication, which improves the data availability and facilitates the file sharing
process without drawing off the local mobile device resources [4]. The data privacy issue is a main
concern in cloud storage system, so the sensitive data is encrypted by the owner before outsourcing
onto the cloud, and data users retrieve the interested data by encrypted search scheme. In MCS, the
modern mobile devices are encountering with many of the security threats as PCs, and various
traditional data encryption methods are imported in MCS [5], [6]. However, mobile cloud storage
system incurs new challenges over the traditional encrypted search schemes, in consideration of the
limited computing and battery capacities of mobile device, as well as data sharing and accessing
approaches through wireless communication. Therefore, a suitable and efficient encrypted search
scheme is mandatory for MCS. Generally speaking, the mobile cloud storage is in great need of the
bandwidth and energy efficiency for data

The Tip Of The Tongue
Abstract
The tip–of–the–tongue (or TOT) phenomenon is the inability to retrieve a specific word, while
typically knowing quite a lot of information about it. In recent years, experimental psychologists
interested in human memory have studied the TOT phenomenon in the hope of better understanding
why this mental process is interrupted as well as any useful techniques for overcoming it. This paper
describes two sets of experiments held at separate American universities. The first set of
experiments investigates which phonological components are capable of facilitating word retrieval.
The second assesses how often a group of subjects could retrieve rare target words on the basis of
their definition alone, while simultaneously comparing semantic and phonological cues for the target
words.
The Tip of the Tongue Phenomenon:
A Momentary Inability to Retrieve Words Stored in Our Memory
The tip–of–the–tongue (or TOT) is an experience involving difficulty retrieving a specific word or
name, while knowing that it is stored in your memory. Individuals experiencing the TOT
phenomenon tend to recall one or more features of the target word, such as the number of syllables it
is comprised of, or its initial sound and letter. People in this state report feelings of anguish and
frustration when searching for the word, and a sense of relief when the word is finally found. For
example, in conversation or in writing you might have had the experience of trying, but failing to

Investigating The Criminal Data Stored On Digital Devices
Abstract: A proliferation in the amount of crimes and crime related data has lead to a demand in
digital forensic investigation tools that helps the investigator to detect, analyze and investigate the
criminal data stored on digital devices. This system introduces a novel subject–based semantic
approach that retrieves a set of top documents that are semantically related to each other
corresponding to the subject defined by the investigator . Keywords: 1.Digital Forensic Investigation
2.Initial Subject 3.Wordnet 4.Synset Introduction: Digital Forensic Investigation is the process of
investigating digital devices for generating evidence related to an incident under investigation.[1]
Task of analyzing this digital data is an essential part for digital forensic tools. Due to an increase in
the amount of digital data the process of analyzing such a large amount of data becomes a time
consuming process. The existing investigation tools provide multiple searching techniques for
analyzing the documents but fail to search for documents of a certain subject or interest.
Therefore,in this system we introduce a digital forensic tool that retrieves those set of documents
that are semantically related to the subject of the investigators interest. The fig. illustrates the digital
forensic process as defined by the DFRWS(Digital Forensic Research Workshop) 1.Identification
phase: Determines the data, components and various entities related to the crime 2.Preservation:
Preserving

Interactive And Engagement Has Impacted Marketing Management
Web 2.0, interaction and engagement is a collection of open–source, interactive and user controlled
online applications expanding the experiences, knowledge and market power of the users as
participants in business and social processes (Constantinides and Fountain, 2008)
This report is based on how the web 2.0, interactive and engagement has impacted marketing
management through the supply chain, distribution and customer date facilitating.
The supply and distribution is focused on the use of advance technology such as GPS tracking and
searching engines, which enables customers to locate firms. Also the supply chain focuses on
creating value through interactive and engagement with other parties within the supply chain and the
end user. Facilitating customer data is based on firms use customer data to identify them, tailor
particular information to them etc.
Main
Distribution and Supply Chain
Distribution
The web 2.0 and other technology advances now enabled firms to find a wide variety of search
engines to find sellers, services, people, location, product information, reviews etc. There are now a
variety of Web search engines such as Kompas business directory, business.com, Yell etc. that
enable buyers both firms and consumer to find each other.
As search engines are becoming more important part in the supply chain firms, it also enables to
change information in their research about the type of distributors, quantity and cost.
Through the web 2.0, search

Project Proposal For An Implementation Of Mobile...
n the MSc report always use third person writing – the only exception is the Academic declaration
section which should be in the first person. Type should be 11 pt for all text, 14pt for chapter titles
and 12pt for section and subsection titles. In the title page you should use 16 pt for the title of the
project, 14 pt for the author's name and 12 pt for affiliations.
Abstract:
This project proposal is a specification and plan for an implementation of mobile application
keywords contextual targeting. The functionality of mobile implementation will live up to several
basic requirements regard to Search Engine Optimisation, Information Retrieval and mobile
application, in an effort to develop a manual keywords phrases clusters. I ... Show more content on
Helpwriting.net ...
Information Retrieval view 8
3.1 Unigram model 8
3.2 Applying methodology to Unigram model 8
4. Mobile application 10
4.1 User Journey 10
4.2 Technical 10
5. Conclusion 11
5.1 Objectives 11
5.2 Schedule 11
Appendix A 11
1. Introduction
One of the ranking factors is how relevant can be your content which represents your web page
according to Google and Bing Page Rank functions. The basic Search Engine techniques for the
content, that can be HTML code. Most of the web pages might not use an appropriate structure of
HTML code [Extra 15], so when a user search a query those web sites can not show as a results on
Google. Because the keywords can not occur in URL and meta tags, the web site is not a result. It
can be part of the results for specific keywords if the web site content has the query 's keywords.
Furthermore, the editor of the web page has to add new keywords or phrases on web page, for
optimizing the web site position on search engine results page. Additionally, mobile applications are
tend to using for search, so I will build a mobile application which provide keywords idea based on
specific Search Engine techniques and Information Retrieval algorithm.

1.1 Aim
The aim of this project is a mobile application that will be helpful for checking Search Engine
techniques (HTML code) and given new keywords ideas to add phrases or keywords on your web
page. My aims are shown below:
To develop a mobile application which will

Essay On Vector
5.4 Compiling Semantic Relationships with Document Vector
Adding hypernyms, hyponyms and synonyms to the document term vector, would lead to
revelations of hidden subjects in the context. So the documents with more common concepts and
ideas have a greater chance to be clustered in the same group. For example, a document about
"‫"موسیقی‬ (music) may have some ideas in a more abstract subject like "‫"هنر‬ (art). The next step after
choosing an appropriate sense for an ambiguous term is adding the inclusion (ISA) and synonymy
relationships of that sense into the vector. One should determine the radius of the hypernyms
(parents) and the hyponyms (children) of the winner synset (sense). The evaluation results for
inclusion of concepts with more ... Show more content on Helpwriting.net ...
(8)
Note that hyper_syni has two terms: tc and td (Fig. 2). td is a new term and the story is just like
inserting tj. The term tc already has a frequency of 3, so the new frequency of tc in d1 would be 5
(3+2).
6. EXPERIMENTAL ANALYSES
In this research the Persian corpus, Hamshahri, is used for the experiments. It is collected in the
database laboratory of the University of Tehran. This corpus is a standard collection that was used at
CLEF for evaluation of Persian information retrieval systems. Also TREC (Text Retrieval
Conference) standards are met in the formal version. The first version includes more than 166
thousand documents. They are collected from Hamshahri Newspaper website archive. They
represent the general texts, spoken and written by Persian natives on a daily basis. In spite of a
rather large number of newsgroups, several ones have more than 1000 documents. These
newsgroups that are used in the evaluations are as follows: economic, politics, sport, social,
literature and art, urban, scientific and cultural, miscellaneous, world news and happenings.
Accuracy (AC) and Normalized Mutual Information (NMI) are used as measures of clustering
quality. In AC calculations, a one to one correspondence between result clusters and input classes is
established. So a function is needed to map or associate the clusters to the input labels. The value of
AC varies between 0 and 1, and a higher value indicates the higher clustering quality. AC is used in
some

Abstract. Scavenging Information Associated To Particular
ABSTRACT
Scavenging information associated to particular person through search engines is one of the most
common activities on the Internet. Result contains numbers of Web pages, which may be relevant to
different person which includes queried name. Human languages are not correct. Text referring to
the city "Roanoke" can mean "Roanoke, Virginia" or "Roanoke, Texas", depending on the
surrounding context. Organizations and companies often have multiple nicknames, name variations,
or common misspellings. Famous persons ("Amitabh Bachchan") often share a name with many
non–famous individuals. In this paper, we propose a similarity measures system to solve the
problem by using cosine similarity which is based on TF and IDF. Web pages having ... Show more
content on Helpwriting.net ...
Changing the infrastructure of the current web to the semantic web.
2. Placing the keyword based search engines as the base and doing some modifications to
considering the query and web page context in order to improve their efficiency. There was a big
problem over the realization of the first idea. The problem was that there were already millions of
millions documents in current web that should apply considerable modifications in their structure to
express their content in RDF and RDFS .
That's why our proposed architecture follows the second strategy.
The goal of Similarity Measures of web pages using Cosine Similarity is to find similarity between
web pages based on extracted entities. For finding Cosine similarity between web pages we extract
entities for each URL by using alchemy API and then find TF–IDF for each entity and every URL
II. LITERATURE REVIEW
Many different approaches have been applied to the basic problem of disambiguation of people and
document ranking they are as follows.
1.Using dependency structure for prioritization of functional test suites [5]in this paper, they
proposed a new test case prioritization technique that uses the dependency information from the test
suites to prioritize. Dependency structure prioritization technique includes four algorithms for
prioritizing. The open dependency proves to have lower execution cost and closed dependency
achieved better fault

The Ontological Files
The authors[7] presented an approach in which ontological profiles are built. Ontology is considered
to be a hierarchy of topics which is used to classify and categorise web pages. It is also used to
identify the topics in which the particular user is interested. Ontology has some existing concepts to
which interest scores are assigned. Keeping the reference ontology, these profiles are maintained
and updated. With observing the ongoing behaviour, a spreading activation algorithm was proposed
for maintaining the interest scores. So this way of the interest scores updation, the most relevant
results are brought on the top.
Each built profile is an instance of this reference ontology. A user profile may comprise of variety of
concepts which is represented as nodes. Each node is represented as a pair (Cj, IS(Cj)),where Cj is a
concept in the reference ontology and IS(Cj)is the interest score annotation for that concept. Every
concept in the profile is provided with an interest score having initial value as one.
The ontological user profile is treated as the network of concepts and the interest scores are updated
based on the activation values. These scores are updated using spreading activation algorithm[8].
Input vector is also involved to represent the current interaction of the user. When the user selects
documents, the user profile is updated and the interest scores of the existing concepts are modified
using spreading activation. by this way the web pages in which the user

Database Management and Information Retrieval
their functionalities. Answer
A database management system (DBMS) is the main software tools of the database management
approach because it controls the creation, maintenance and use of the databases of an organization
and its end users. Information retrieval is a system that to provide the relevant information based on
the user needed. This process can be find through the passwords or keywords or query from the
users. Beside provide or find the relevant information towards the query, information retrieval also
make a ranking toward the information. Every document that are provided will have the ranking and
the information that have highest ranking will be known more relevan rather than others.
Information retrieval act as intermediation between the user and the information provided.
Database Management System Information Retrieval
1. Data dictionary. The database management system has been perform management function to the
elements in the database and how to connect the other data. To access the data basically it through it
through the database management system. this is will make easy to the user to search the data. 1. To
identify the information relevan to the areas of interest of the target user`s community.
2. Backup and recovery management. Through this function, it can help to prevent the outside threat
to the database. Database management system can restore the

Database Management Systems
Question 1: Differentiate between database management system and information retrieval system by
focusing on their functionalities.
Database management system (DBMS) is an application which interacts with the database at some
point in its execution. While, the Information Retrieval System (IR) is the activity of gathering
information resources which related to information need from a collection of information resources.
Usually, we use metadata or full–text indexing in order to make a search on data requires.
Information Retrieval Systems are used to overcome what has been called as "information
overload". Many universities and public libraries use Information Retrieval System to provide
access to books, journals and other documents. For instance, Web search engines such as Google,
Yahoo and Bing, are the most visible IR applications.
There are several functions that DBMS performed to make sure the integrity of the data and data
consistency in the database such as data storage, retrieval and update, A user–Accessible catalogue,
transactional support, concurrency control services, recovery services, Authorization services,
support for data communication, integrity services, services to promote data independence and
utility services.
Meanwhile, an information retrieval process begins when a user enters a query into the system.
Queries are formal statements of information needs, for example search strings in web search
engines. In information retrieval a query does not

A Survey On Friend Recommendation Essay
A Survey on Friend Recommendation in a Social Bookmarking System
Bhavesh Jain1, Tejas Kadiya2, Ramesh Prajapati3, Dr.Samrat Khanna4
1M.E Computer Engineering Student, IIST–Rajpur
2Assistant Professor, IIST–Rajpur
3Dept. of Computer Science Engineering, Rai University, Dholka
4Dept. of Information Techmology, V.Vnagar
Abstract–The technique of Collaborative Filtering is especially successful in generating
personalized recommendations. Collaborative Filtering is quickly becoming a popular technique for
reducing information overload, often as a technique to complement content based information
filtering. More than a decade of research has resulted in numerous algorithms, although no
comparison of the different strategies has been made. In fact, a universally accepted way of
evaluating a Collaborative Filtering algorithm does not exist yet. In this survey, we explain different
techniques found in the literature, and we study the characteristics of each one, highlighting their
principal strengths and weaknesses. This Paper Present a new user similarity model to improve the
recommendation performance to calculate the similarity of each user. The model not only consider
the local context information of user rating but also the global preferences of user behavior.
Index Terms–PCC, Jaccard, MSD, cold–start, Proximity, Sigmoid
I. INTRODUCTION
The Internet, with hundreds of millions of pages worldwide, has become the greatest source of
information that has ever existed. In

The Challenges For Students Today
Writing a research paper can be one of the toughest challenges for students today. A huge obstacle to
success is locating and navigating different databases and making sure that research sources are
credible and scholarly. We are lucky, in that CSU Global Library has given its students access to
several different databases, making it easier to navigate vast amounts of information. I found two
different databases that I feel will be helpful with my two areas of interest, healthcare management
and clinical research. The first database is EBSCO. It is a database with a broad range of topics. It
includes information on health care, corporations, business, government and military and includes
links to public libraries as well as links to information that will be helpful for K–12 students. The
second database is PubMed. Where EBSCO was a database filled with information on a broad range
of topics, PubMed is more streamlined and contains information on biomedical sciences. PubMed
comprised over 26 million citations from biomedical literature, MEDLINE, books and scientific
journals. EBSCO Search Engine When starting at the CSU Global Library's main page, EBSCO's
first search cannot be narrowed down. It is a simple word or topic search, but once a general topic is
entered a more defined search can begin. The database allows you to use multiple topic expanders
and limiters to narrow down the information you are looking for. You can search for full text articles
or search

Annotated Bibliography On Digital Libraries
I. INTRODUCTION The rapid increase in the volume of digital libraries due to cell phones, web
cameras and digital cameras etc, needs and expert system to have the effective retrieval of similar
images for the given query image [1]. CBIR system is one of such experts systems that highly rely
on appropriate extraction of features and similarity measures used for retrieval [10]. The area has
gained wide range of attention from researchers to investigate various adopted methodologies, their
drawbacks, research scope, etc [2–5, 14–18]. This domain became complex because of the
diversification of the image contents and also made interesting. [10]. The recent development
ensures the popularity of CBIR, since it has been applied in many real world applications such as
life sciences, environmental and health care, digital libraries and social media such as facebook,
youtube, etc. CBIR understands and analyzes the visual content of the images [20]. It represents an
image using the renowned visual information such as color, texture, shape, etc [11, 12]. These are
often referred as basic features of the image, which undergoes lot of variations according to the need
and specifications of the image [7–9]. Since the image acquisition varies with respect to
illumination, angle of acquisition, depth, etc, it is a challenging task to define a best limited set of
features to describe the entire image library. Similarity measure is another processing stage that
defines the performance of

Curse of Dimensionality Makes CBIR System is Necessary...
This is known as 'Curse of Dimensionality', which states that the number of examples necessary to
reliable generalization grows exponentially with the number of dimensions. Learn ability
necessitates dimensionality reduction, which is the process of reducing the number of random
features under consideration during image retrieval (Roweis and Saul, 2000).
In large multimedia databases, high–dimensional representation is computationally intensive and
most users are unwilling to wait for results for a long time. Thus, for storage and retrieval efficiency
concerns, dimensionality reduction in CBIR systems is necessary. Example of these techniques
includes Principal Component Analysis (PCA), Independent Component Analysis (ICA) and Linear
... Show more content on Helpwriting.net ...
1.3.4. Indexing
When manipulating massive image databases, a good indexing is necessary. Processing every single
item in a database, when performing queries, is extremely inefficient and slow. When working with
images, the feature vectors are used as the basis of the index. Popular multi–dimensional indexing
methods include the R–tree and the R*–tree algorithms (Long et al., 2003). The Self Organizing
Map (SOM) is also one of the indexing structures (Laaksonen et al., 2000). Usage of indexing
techniques during searching reduces processing time and thus retrieves images quickly.
1.4. PRACTICAL APPLICATIONS OF CBIR
Research and development issues in CBIR cover a range of topics which shares with mainstream
image processing and information retrieval. Some of the most important are:
to understand image users' needs and information–seeking behaviour
to identify suitable ways of describing image content
to extract features from raw images
to provide compact storage for large image databases
to match query and stored images in a way that reflects human similarity decisions
to efficiently access stored images by content
to provide usable human interfaces to CBIR systems
A wide range of possible applications for CBIR technology has been identified (Gudivada and
Raghavan, 1995). This section presents

The Challenges For Students Today
Writing a research paper is one of the toughest challenges for students today. An obstacle to success
is locating and navigating different databases and making sure that research sources are credible and
scholarly. We are lucky, in that CSU Global Library has given its students access to several different
databases, therefore, making it easier to navigate vast amounts of information. I found two different
databases that will be helpful with my two areas of interest, healthcare management and clinical
research. The first database is EBSCO. It is a database with a broad range of topics. It includes
information on health care, corporations, business, government and includes links to public libraries
as well as links to information that will be helpful for K–12 students. The second database is
PubMed. Where EBSCO was a database filled with information on a broad range of topics, PubMed
is streamlined and contains information on biomedical sciences. PubMed contains over 26 million
citations from biomedical literature, MEDLINE, books and scientific journals. EBSCO Search
Engine When starting at the CSU Global Library's main page, EBSCO's first search results cannot
be reduced. It is a simple word or topic search, but once a general topic is entered a better defined
search can begin. The database allows you to use multiple topic expanders and limiters, therefore,
narrowing down the information you are searching. Students can search for full text articles or
search for

Personalizaton through Searches on Google and Facebook is...
Worldwide there is an underlying issue within search engines and social media. This issue is
becoming evident as the number of people retrieving their news through Google and Facebook
increases. Personalisation through searches is evolving to only show the consumer what they want
to see not what they need to see. Online Organiser and Author of 'The Filter Bubble', Eli Pariser
argues in his TED Talk about the unreliability of not being exposed to information that could
broaden our worldwide view and possibly resolve pivotal democratic issues. This cycle of trying to
consistently please the users is becoming evident within search organisations and has evolved with
technology as algorithmic filters were introduced having an unbalanced and unethical filter. This
invisible filter is now generating a "personal unique universe of information" (Pariser, 2011), for
every individual user, enforcing the inability to have a functioning democracy because of the public
not receiving accurate and most importantly balanced information. The Filter Bubble's motive is to
create a personalised environment online through the search engine, by getting to know the source
of sites it thinks it's consumer is interested in. The filter then only provides their subject with
specific 'relevant' information. The continuous flow of information being shown on google and
Facebook revolves around the commonly visited sites rather than things that benefit the users
worldwide view and get them thinking (Eli

Google Makes People Smarter?
Google Makes People Smarter
People are adapting, and changing their approach of how they seek knowledge: From hours, and
hours of researching in the library to find information, to a five–second research on the internet with
a click of a button? In an ever–changing world, humans are evolving with the ease of technology.
The google search engine allows the users to search anything with the tip of their fingers. The World
Wide Web has billions of website with information. People can search anything they want to know
about. The innovation of the Google search engine surpassed its competitors because of its
sophisticated algorithm. Is the Google search engine changing the way we think? Some people
believe Google is making people stupid because ... Show more content on Helpwriting.net ...
According to the article, Google was initially called BackRub, but was changed to Google in 1997;
"a mathematical term called googol, which is the numerical one followed by one hundred zeros"
(Keeline 510). The term reflects Page, and Brin 's mission to organize an infinite amount of
information on the web. In 1998, PC Magazine named Google the top search engine in its Top 100
Web Site because of the search engine 's "uncanny knack for returning extremely relevant results"
(Keeline 510). The report from PC Magazine gave Google its first recognition in public. In 2006,
Google became so popular that the word google was added as a verb to Merriam–Webster Collegiate
Dictionary, and Oxford English Dictionary. Both dictionaries listed the word as "to search for
information on the Internet using the Google search engine" (Keeline 510). Google search engine
separated itself from its competitors because of its relevant search results.
What makes the Google search engine great, and reliable to search for information? Simply put,
Google uses a superior algorithm. An algorithm is a step–by–step instructions for solving a problem.
The Google search engine returns relevant results making it a reliable source of information. The
Google search engine is the best at selecting links that match the users search query. A January 2013
article in Electronics For

Analysis of Database Management and Information Retrieval...
1. DIFFERENCES BETWEEN DATABASE MANAGEMENT SYSTEM AND INFORMATION
RETRIEVAL SYSTEM
DATABASE MANAGEMENT SYSTEM (DBMS) INFORMATION RETRIEVAL SYSTEM (IRS)
DBMS offer advance Data Modelling Facility (DMF) including Data Definition Language and Data
Manipulation Language for modelling and manipulating data. IRS do not offer an advance DMF.
Usually data modelling in IRS is restricted to classification of objects.
Data Definition Language of DBMS is the capability to define the data integrity constraints. In IRS
such validation mechanisms are less developed.
DBMS provides precise semantics. IRS most of the time provides imprecise semantics.
DBMS has structured data format. IRS is characterised by unstructured data format.
Query specification is ... Show more content on Helpwriting.net ...
3.1 COMPONENTS OF INFORMATION RETRIEVAL SYSTEM
Diagram above shown the components of an information retrieval system. There are three
components which is input, processor and output.
Starting with the input, when the retrieval system is online, it is possible for the user to change his
request during one search session in the light of a sample retrieval, thereby it is hoped that
improving the subsequent retrieval run. Such a procedure is commonly referred to as feedback.
The processor the part that retrieval system concerned with the retrieval process. The process may
involve structuring the information in some appropriate way. It will also involve performing the
actual retrieval function which is executing the search strategy in response to a query. In the
diagram, the documents have been placed in a separate box to emphasis the fact that they are not
just input but can be used during retrieval process. Finally come to the output which is usually a set
of citations or document number. 4. DIFFERENCES BETWEEN STRUCTURED AND NON
STRUCTURED DATA
4.1 STRUCTURED DATA
The structured data means data that could be identified because it is organised in a structure. The
standard form of structured data is a database where particular information is stored based on a
methods of columns and rows. Structured data also can be look up by data type within content.
Structured data is understood by computers and is also efficiently

The And Reverse Engineer The World Wide Web
Not many people know that Google started out as BackRub, not the relaxing kind that you get at a
spa. The idea for BackRub came from Larry Page looking for a topic to do his doctoral thesis on.
Page decided to try and reverse engineer the World Wide Web for his thesis. Little did they know
that were on the way to creating one best "Good to Great" companies of this century. As Jim Collins
states in Good to Great that the companies that go from good to great are not looking for the quick
fix and Google definitely wasn't looking for that. In fact, they were not even trying to make an
internet search engine at all. Their goal was to look at the World Wide Web similar to the way
academic build their papers, on citations. Papers are judged not only on the number of citations they
use but also the number of times they are cited. Instead of using citations they used web links to
other sites and developed a ranking system. As John Battle states in his article for Wired.com "As
they fiddled with the results, Brin and Page realized their data might have implications for Internet
search. In fact, the idea of applying BackRub 's ranked page results to search was so natural that it
didn 't even occur to them that they had made the leap." The idea for what would become the biggest
World Wide Web search engine was born. Page and Brin's decision to keep it as just a search engine
is what created the companies hedgehog. Popular search engines at the time, Lycos and Alta Vista,
were

The Information Assessment Method
Many clinically relevant research studies are published daily; thus, it is difficult for physicians and
pharmacists (indeed all healthcare professionals) to find the time to absorb this new knowledge.
Electronic knowledge resources, specifically the pre–appraised evidence resources, can help family
physicians in two ways. These resources provide clinical information to answer clinical questions at
the point of care (Pull Technology) (e.g. Up–To–Date and Essential Evidence Plus), and they raise
awareness of new research through information delivery systems (Push Technology) (e.g. Daily
POEMs and e–Therapeutics+ Highlights educational emails). These EKR are credible pre–appraised
evidence resource summarizes and provides evidence–based clinical recommendations which are
the results of research studies that have been selected for clinical relevance and critically appraised
for methodological quality. These resources: (i) are selected based on evidence grading methodology
and criteria, (ii) present the date of evidence review for each piece of information, (iii) correlate the
treatment recommendations to the specific evidence, and (iv) are continuously revised and updated.
The value of information can be conceptualized as, the acquisition of information, associated
cognitive impact, its use or application and, information related patient health benefits (1, 2). The
presence of a feedback system can enable researchers to assess the value of information: the reasons
why

1. Functions of a Database Management System
Database Management System (DBMS) Information Retrieval System (IRS)
Storage, Access And Provide
DBMS provide services such as storage, access and update data in the database. Acquisition of the
necessary and appropriate documents.
Provide Free Catalog
DBMS provides a catalog that contains information about the data and catalogs that can be accessed
by users. Preparation and representation of the content of those in documents.
Supports Transactions
The transaction is a unit of work that contains several commands up–date the data. Coding of the
content indicators.
Concurrency control
Database Management System (DBMS) to ensure accurate updated database correctly if many users
update the database simultaneously. Organized storage of those documents and their indicators in
separate files.
Recovery From Failure System
Database Management System (DBMS) provides facilities to restore the database in the event of
damage Development of operational search strategies.
Authorization Services
The facility is to ensure that the right people are allowed to achieve its data. Physical dissemination
of the retrieval result.
Utility Services
Facilities for maintaining databases through data editing, deletion of records, build new files and so
on.
Integrity Services
Change data must follow the constraints or conditions that have been determined. This facility is to
maintain data consistency.
2. 0 Differences between

A Brief Note On Image Based Qa On The Video And Audio...
C. Image Based QA: An image–based QA approach was introduced in [11], which mainly focuses
on finding information about physical objects. An image–based QA system allows direct use of an
image that refers to the object. This type of systems was designed to find multimedia answers from
web–scale media resources such as
Flicker, Google images.
D. Multimedia QA Search: Due to the increasing amount of digital information stored over the web,
searching for desired information has become an essential task. The research in this area started
from the early 1980s. With the rapid growth of content analysis technology in the 1990s, these
efforts rapidly expanded to tackle the video and audio retrieval problems. Fig. 3 shows an example
of MMQA.
Fig 3: ... Show more content on Helpwriting.net ...
Li and
Roth [12] developed a machine learning approach that uses the SNoW learning architecture to
classify questions into five coarse classes and 50 finer classes.
They used lexical and syntactic features such as partof– speech tags, chunks and head chunks
together with two semantic features to represent the questions.
Zhang and Lee [13] used linear SVMs with all possible question word grams to perform question
classification. Arguello et al. [14] investigated medium type selection as well as search sources for a
query. It analyzes question, answer, and multimedia search performance. Then learn a linear SVM
model for classification based on the results.
1.1 Question–Based Classification: Since many questions contain multiple sentences and some of
the sentences are uninformative. The classification is accomplished with two steps. First, we
categorize questions based on interrogatives second, for the rest questions; we perform a
classification using a naive
Bayes classifier.
Table I Representative interrogative words
1.2 Answer–Based Classification: Apart from questions, answer can also be an important clue. For
answer classification bigram text features and verbs are extracted. With the help of verb it will be
easy to judge whether the answer can be related with video content.Intuitively, if a textual answer
contains many complex verbs, it is more likely to describe a dynamic process and thus it has high
probability to be well answered by videos. Therefore, verb can

Data Analysis And Image Based Recommendation Sorted By The...
Abstract– Query and Image based recommendation sorted by the method of re–ranking provides an
accurate output of images based on the visual semantic signatures of the query image .In query
based recommendation, keyword expansions help provide better results whereas in image
recommendation, re–ranking based on priority of images accessed by other users provides more
accurate results. This paper presents an Android application with basic features comprising of an
image recommender system which provides a text as well as image based output on the type of
query provided by the user. The input can also be text based or image based. The results obtained
are re–ranked and prioritized according to user intention and also differ with respect to different
users. The information of users search interests are stored offline and a profile based system is
maintained for each and every user so that accurate results are obtained for different users working
on the same device.
Keywords– Smartphone image recommender, image recommender, profile base image
recommender, image re–ranking.
I. INTRODUCTION
The primary objective of this paper is to provide accurate search results based on keyword
expansion as well as comparing the semantic signatures of images to provide re–ranked images for
the android operating system. Such a system is not yet available in
Smartphone devices especially android but it exists for the Apple OS commonly known as IOS. The
application will feature a search box
for

Statement Of Mechanical Engineering
STATEMENT OF PURPOSE
I am Nileshkumar Luhar. Discovering and understanding how certain mechanical products work
have attracted my attention for the longest time. I have been watching TV show named How It's
Made on the Discovery Channel since last six years. Seeing the manner in which the machineries
and cars are built and the various processes involved instilled desire in me to be part of the whole
process. I felt that Engineering would be the area, which would give me the opportunity to learn and
explore how the fundamentals of science are applied to create technology for practical and real
purposes. This coupled with a natural flair for science and mathematics motivated me to take up
Mechanical Engineering in University.
Mechanical engineering is a diverse subject that derives its breadth from the need to design and
manufacture everything from small individual parts ... Show more content on Helpwriting.net ...
Moreover, my innate strengths have always been creative abilities and power of imagination; which
made me take up a discipline that would allow me to channel them in the best possible way. I have
finished my bachelor of technology in mechanical engineering with 8.75 CGPA out of 10. Subjects
like Elements of Mechanical Engineering, Kinematics and Dynamics of Machines, Strength of
material, Manufacturing Processes, Mechanical Design & Analysis, Mechanical Vibrations etc.,
revealed to me limitless horizons in the field of Mechanical Engineering. We are in an era of global
and technological changes where boundaries are fast disappearing and the greatest challenge
tomorrow holds for us in to manage continuity of change. To satiate my curiosity and to fulfill my
ambitions I have decided to pursue a masters program in Mechanical Engineering.
I have

Common Facets for Indexing of Enterprise Entities on...
1 Introduction
The research question this paper are meant to answer is: what are the main characteristics of
enterprise information which are common to different companies?
Certainly, there are common characteristics of information in some companies, but the identification
of common attributes in the whole enterprise domain requires a domain analysis.
All the companies depend on information to do work and to make decisions.
And even different companies do common tasks and have similar organizational units such as
finance, human resources, information technology, marketing and customer relationship.
However, even so similar companies can refer differently to subjects1 in different economies and in
different units (e.g. intern as a student/client for a university; intern as a student employee for an
engineering firm; and intern as a worker, employee, or volunteer for the law).
The generalisation of enterprise domain is challenging and it faces three main obstacles.
First of all, companies are uncomfortable to publicly expose their data as most of their information
are classified, strategic or sensitive, exposing clients, employees, partners and future plans
(TRECENT).
Additionally, the adoption of any company data is unreliable to represent the whole enterprise
domain and support the project of more efficient enterprise information retrieval systems for all the
other companies (informationIntegration05).
And finally, once empiricism does not answer why and how long the

The Non Technical Aspects Of Search Engines And Their Uses
To be sure, the non–technical aspects of search engines and their uses is not uncharted territory.
Depending on how widely one casts the net, one can find considerable relevant work in past
literature across fields. For example, researchers in the areas of library and information science have
been interested for a long time in how people find material using various interfaces and databases,
and these projects are not unrelated to the questions addressed by the articles in this collection (for a
review of some of this work, see Bar–Ilan, 2003; Hsieh–Yee, 2001). However, work in this domain
often only focuses on very small and non–representative samples and rarely considers the social
context of searching (for a more elaborate discussion of ... Show more content on Helpwriting.net ...
We also have evidence suggesting that search engine users are not particularly savvy about the
behind–the–scenes of search engines. For example, when asked in one study whether they were
aware of the distinction between paid and unpaid results, the majority (62%) indicated that they
were not (Fallows, 2005). These findings were mirrored by another report asking similar questions
in which 56% did not know the difference between the two types of results (iCrossing, 2005).
Moreover, the latter findings suggested that this know–how is not randomly distributed among
users, but rather that men and younger adults claimed to be more informed about this aspect of
search engines than women and older users. Regarding the role of search engines in channeling user
attention, although researchers started considering the possible gatekeeping implications of these
services years ago (Hargittai, 2000; Introna & Nissenbaum, 2000), little empirical work has
followed to examine the extent to which search engines may or may not discriminate against certain
types of content while (perhaps unduly) favoring others. Some case studies have examined the
censorship of certain types of material by some search engines in particular national contexts (e.g.
Finkelstein, 2004; Zittrain & Edelman, 2002), but there is little systematic work considering less
controversial

Cornelis Joost van Rijsbergen one of the big name in IRS...
Cornelis Joost van Rijsbergen one of the big name in IRS field nowadays. Born in year 1943 at
Rotterdam, Holland, he now still alive with age 71 years old. He also known as C.J.Keith van
Rijsbergen, was educated in Holland, Indonesia, Namibia and Australia. C. J. Keith van Rijsbergen
is a degree holder in Mathematics. He took a degree in mathematics at the University of Western
Australia. After graduated, he spent two years tutoring in mathematics whiles further his study in
computer science. He took Computer Science at Cambridge University for PHD level. In 1972 he
completed a PHD. When we look back on his study background, there are no directly related what
he was studied with information retrieval field. But the fact, C. J. Keith van ... Show more content
on Helpwriting.net ...
Besides become an editor, Professor van Rijsbergen also becomes an advisor to GMD, Director of
Itext Ltd, Inforythmics Ltd (IT mutimedia companies). Professor van Rijsbergen also becomes a
Fellow of the Royal Academy of Engineering, Royal Society of Edinburgh, IEE, BCS, and ACM.
From year 1993 until 2000, he works as an Editor–in–Chief of The Computer Journal. He also
Associate editor of Information Processing and Management, on the editorial board of Information
Retrieval, and on the advisory board of the Journal of Web Semantics. Other that this, he also take
part as a Programme committee member and editorial board member of the major IR conferences
and journals. In year 2003 he become a Fellow of the Association for Computing Machinery. After
that, since 2007 he is Chairman of the Scientific Board of the Information Retrieval Facility.
This is a part of his professional activities beside his routine job at university. Gradually in
Mathematic field, further study in computer science, then become a professional in Information
Retrieval field. All these process bring Professor van Rijsbergen into great employment experiences.
Professor van Rijsbergen start involve in writing research since year 1969. From that year until
nowadays, reader can identify research that Professor van Rijsbergen wrote because it has his own
style in writing. His research covered both theoretical and experimental

Annotated Bibliography On Information Retrieval Systems
Librarians have duties to design, query, and evaluate information retrieval systems. In order to do
so, librarians must understand each basic element of an Information Retrieval System. The first step
is to understand their purpose. Information Retrieval Systems are designed to deal with various
sources of information, and to satisfy user's requirements. When a user makes an inquiry, the system
must analyze the available sources, match the search specifications, and retrieve the items which are
the most relevant to the search terms. Chowdhury (2004) describes the three aspects of Information
Retrieval System design: the document subsystem, the user subsystem, and the searching/retrieval
subsystem. Together, these three subsystems work to store, maintain, and sort information items.
These systems are in place in many areas of libraries. They can be found in privately held databases,
Open Public Access Catalogs (OPAC), and paid subscription databases. OPACs may be confined to
a single library or they may be jointly managed by a wider library district or by a collaboration of
medical or academic libraries. They hold a great deal of information about the physical and the
digital library collection. They allow users to retrieve information concerning the location of where
information items are to be found. Without a well functioning OPAC, it would be very difficult for
both librarians and patrons to access the information items held in library collections. OPACs hold

A Study On The Mapping Process Of Mapping The Coordinates...
ABSTRACT Named entity disambiguation is a very interesting problem having wide ranging
applications. It is the process of mapping the mentions of persons, organisations, events etc. in
textual documents to real world entities. The mapping process becomes tedious when these
mentions in the text are commonly used to describe more than one real world entities. It is then said
that the mention is ambiguous. If the mentions can be correctly mapped to the corresponding real
world entities, then it can lead to a more informative and intuitive web experience where the textual
documents can be linked to other knowledge bases which contain more information on various
entities described in the document. In this report, we have surveyed well known research papers in
the field of named entity disambiguation and have described the approaches suggested in them.
Successive sections of report aim to solve the shortcomings of the algorithms discussed in the
previous sections. INTRODUCTION The recent years have seen a huge increase in the number of
online documents. This has resulted in a huge amount of information being available at the click of a
mouse. But, at the same time, the retrieval of relevant information from this collection of
unstructured documents has emerged as a challenging task and is a topic of research. A major part of
retrieving information out of a document is finding out the words or phrases of significance in the
article like the persons, organization, location,

their functionalities.
Answer:
What is database management system? Database Management System is a database program. The
DBMS manage incoming data, organize it, and provided ways for the data to be modified or extract
by users or other programs. This cause, most database software comes with an Open Database
Connectivity (ODBC) driver that allows the database to integrate with other databases. For example,
common SQL statements such as SELECT and INSERT are translated from a program's proprietary
syntax into a syntax other databases can understand. Some DBMS examples include PostgreSQL,
MySQL, SQL Server, Microsoft Access, Oracle, FileMaker, RDBMS, dBASE, Clipper, and FoxPro.
It is a software system that uses a standard method of retrieving, and running queries on data.
What is information retrieval system? Informational Retrieval System is the activity of obtaining
information resources relevant to an information need from a collection of information resources.
Web search engines are the most visible. Search can be based on metadata or on full–text (or other
content–based) indexing. Automated information retrieval systems are used to reduce what has been
called "information overload". Many universities and public libraries use IR systems to provide
access to books, journals and other documents.
Differences between database management system and information retrieval system by

Document Analysis Using Latent Semantic Indexing With...
Document Analysis Using Latent
Semantic Indexing with Robust Principal
Component Analysis
Turki Fisal Aljrees
School of Science and Technology
Middlesex University
Registration report
MPhil / PhD
June 2015
Acknowledgements
I would like to acknowledge Director of Study Dr. Daming Shi, My Second Supervisor: Dr.
David Windridge , and Dr. George Dafoulas
Abstract
There are numerous data mining techniques have been developed and used recently in text
documents. Using and update discovered a pattern effectively is still an open research topic,
especially in the text mining area. Measuring the similarity between documents is an important
operation in the text processing field. Latent Semantic Indexing (LSI) will be adapted to obtain a set
of ... Show more content on Helpwriting.net ...
how to discover subtle relationships that might exist between the documents by applying
dimensionality reduction to remove noise from the data and better apply the statistical data mining
methods in any given the collection of documents will be tested .
The phrase–based document similarity approach to compute the pair–wise similarities of documents
based on the Suffix Tree Document (STD) model will experimented in. The results will show that
the performance obtained by the proposed measure should be better than that achieved by other
measures, and the similarity between two sets of documents will evaluated on several real–world
data sets for specific problems.
Table of Contents
List of Figures ix
List of Tables xi
Abbreviations xiii
1 Introduction 1
1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

1.2 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
1.3 Research Objectives and Question . . . . . . . . . . . . . . . . . . . . . . 7
2 Literature Review 9
2.1 Information retrieval and text mining . . . . . . . . . . . . . . . . . . . . . 9
2.1.1 Text retrieval and Text Preprocessing . . . . . . . . . . . . . . . . 9
2.1.2 Text representation . . . . . . . . . . . . . . . . . . . . . . . . . . 10

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