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ABSTRACT

The amount of information available today is extremely large. The increasing need for easier
and faster information discovery demands optimal information retrieval techniques. A
measure of performance of any information retrieval system is based on the effectiveness
and efficiency of retrieval. While some techniques rely on algorithms that improve search,
others aim at increasing user’s ability to formulate search queries. Here we present a nonpredefined
query model for information retrieval system based on a relational database.

 

 

TABLE OF CONTENTS

Abstract……………………………………………………………………………………….ii
Dedication……………………………………………………………………………………iii
Acknowledgement…..……………………………………………………………………….iv
Table of contents………………….………………………………………………………….v
List of figures……………………………………………………………………………….vii
List of tables………………………………………………………………..……………….vii
1. Introduction……………………………………………………………………………….1
1.1 Research context………………………………………………………………….2
1.2 Problem statement……………………………………………………………….2
1.3 Research objectives…………………………………………………..………….3
1.4 Research methodology…………………………………………………….…….3
1.5 Organization of work…………………………………………………………….3
2. Literature review………………………………………………………………………….4
2.1 Information Retrieval…………………………………………………………….4
2.2 Data or information retrieval? ………………………………………….……….8
2.3 IR Models……………………………………………………………………….10
2.4 Boolean Retrieval……………………………………………………………….11
2.5 Data warehousing……………………………………………………………….13
2.6 Human-Computer Interface…………………………………………………….14
2.6.1 User interfaces for search by Marti A. Hearst……………………….14
2.6.2 Designing the User Interface by Ben Shneiderman………………….15
2.6.3 Models of Interaction…………………………………………..…….16
2.6.4 Design of Search Interfaces………………………………………….17
2.7 Related Works………………………………………………………………….18
2.7.1 A. David, D. Bueno, P. Kislin, Case-Based Reasoning, User model and IRS.18
vi
3. Research proposal……………………………………………….……………………….21
3.1 Information Retrieval System…………………………………………………..21
3.2 Non-predefined Query Model…………………………………………………..22
3.3 Interface for IR……………………………………………………………..……24
3.4 Design Specifications…………………………………………………………..26
4. Case study………………………………………………………………………………..32
4.1 Employee Records……………………….……………………………………..32
4.2 Data Modeling…………………………………………………………………..32
4.2.1 Entity-Relation (ER) Model…………………………………………..33
4.2.2 Graph of Relations…………………………..………………………..34
4.2.3 Dictionary of Attributes…………………………………..…………..35
4.2.4 Dictionary for Query……………………………………..…………..35
4.3 Cross Tabulation………………………………………………………………..38
5. Conclusion……………………………………………………..………………………..43
5.1 Contributions…………………………………………………………………..43
5.2 Perspectives…………………………..………………………………………..43
References…………………………………………………………………………………..44

 

 

CHAPTER ONE

INTRODUCTION
Information retrieval is obtaining information by searching a repository for items that match
user’s information need. According to Losee (1998), retrieval systems often order documents
in a manner consistent with the assumptions of Boolean logic, by retrieving, for example,
documents that have the terms dogs and cats, and by not retrieving documents without one
of these terms. Systems consistent with the probabilistic model of retrieval locate documents
based on a query list of terms, such as {dogs, cats}, or may accept as input a natural language
query, such as I want information on dogs and cats. A probabilistic system then ranks
documents for retrieval by assigning a numeric value to each document, based on the weights
for query terms and the frequencies of term occurrences in documents.
We want to know how to “best” formulate a query, and our ultimate interest in measures of
human utility: how satisfied is each user with the results the system gives for each information
need that they pose? Manning et al (2009). Most everyday users of IR systems expect IR
systems to do ranked retrieval, unfortunately relevance ranking is often not critical in Boolean
systems. On the other hand, most IR systems rank documents by their estimation of the
usefulness of a document for a user query, and there is little or nothing a user can do about
it. However, many power users still use Boolean systems as they feel more in control of the
retrieval process.
It is correct that the set of retrieved documents are not ranked in Boolean searches. However,
the cost of a ranked set is a set that is not fully controlled or understood by the user. In
Boolean searches, the user obtains well‐defined search sets, which is a clear advantage if
searching is considered a learning process. The well‐defined set provides better feedback and
therefore allows modified search profiles. Hjørland (2014).
Conventional IR systems are built on the Boolean model while most IR systems rely on
sophisticated algorithms for better ranking. Most of the materials for ranking are usually
documents of an unstructured nature (usually text). Today, research in the field IR are split
2
among various activities and between (a) optimizing algorithms for ranked systems and (b)
extending the Boolean model to increase the selection power of users.
Researchers who are working on the storage side of the information retrieval system are
engaged in designing sophisticated methods for identification and representation of the
various bibliographic elements essential for documents, automatic content analysis, text
processing and so on. On the other hand, researchers working on the retrieval side are
attempting to develop sophisticated searching techniques, user interfaces, and various
techniques for producing output for local as well as remote users. Chowdhury (2004).
1.1 Research context
The area of study is within the domain of Information Retrieval. IR is a broad area and an
important aspect of life. The recognition of the important role information plays in our daily
lives has led to an outburst of studies aimed at advancing the field of IR.
Although recent efforts in IR are largely towards the web search, Boolean search is arguably
the best search strategy for exact‐match information retrieval. One of the criticisms against
the Boolean search is that most searchers do not have the skills required to formulate Boolean
query. But what about simplifying the Boolean search through a better human‐computer
interaction? And what about expert searchers who would prefer having full control that only
Boolean search provides?
This work is based on the Boolean search of structured information stored in a relational
database. More emphasis is on the user interface that simplifies formulating Boolean query
and access to relevant information.
1.2 Problem statement
Classical IRS have predefined query interface in which the user’s needs are anticipated and
the associated query implemented the IRS. The issue here is on what happens to “ignored”
needs that arise after the development of the IRS, based on a relational database.
3
1.3 Research objectives
The aim of this project is to propose a model that will allow an IRS to provide an open query
interface, based on a relational database.
This work is user‐centric and so much effort would go into developing the user interface
suitable for building dynamic queries.
Lastly, it is expected that it would be possible to query for cross tabulation analysis using our
query interface.
1.4 Research methodology
A review of existing literature in Information Retrieval provides a head start for this work. A
related work in this area is that of Olubunmi AKINTADE on “Case Based Reasoning in
Information Retrieval System: Principles, Evolutions and Applications”, 2007.
A model is proposed that gives searchers full control over the search process. This is followed
by developing the query interface ideal for the model.
Microsoft .NET Framework is used to develop the user interface. The choice is influenced by
the need to use Excel API to visualize crosstab results.
1.5 Organization of work
This research centres on ad‐hoc Information Retrieval. It is organized as follows:
The next chapter gives a brief overview of the key advances in the field of Information
Retrieval, and a description of where the state‐of‐the‐art is at in the field. The third chapter
introduces the proposed model and design specifications for the user interface. The forth
chapter presents a case study for implementation using our model and query interface. The
Conclusion is a summary of contributions and challenges to provoke future work in the field
of Information Retrieval.
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