Information Retrieval: Models and Concepts

Dr. Badal Soni, Dr. Suganya Devi K.

ISBN: 9789354246791

252 pages


INR 429


Information Retrieval Models and Concepts is a comprehensive book that educates on both the fundamental ideas and the rapidly expanding reach of Information Retrieval (IR) as a field. It presents an introduction to the fundamental topics underlying modern search technologies. This book includes algorithms, different data structures, indexing techniques, retrieval, and evaluation parameters. It addresses all kinds of concepts, algorithms-related IR for research purposes, especially in the Web search engine domain.

Chapter 1 Fundamental of Information Retrieval

1.1 Introduction

1.2 Blocked Sort-Based Indexing

1.3 Single-Pass In-Memory Indexing

1.4 Distributed Indexing

1.5 Dynamic Indexing

1.6 Advanced Indexing


Chapter 2 Information Retrieval Evaluation

2.1 Introduction


Chapter 3 Boolean Information Retrieval Model

3.1 Introduction

3.2 What Is Boolean Retrieval?

3.3 Representation of Boolean Model


Chapter 4 Vector Space Information Retrieval Model

4.1 Introduction

4.2 What Is Document Similarity?

4.3 Cosine Similarity

4.4 TF-IDF Weighting

4.5 What Is Named-Entity Recognition?

4.6 State-of-the-Art NER Models


Chapter 5 Probabilistic Information Retrieval Model

5.1 Introduction

5.2 Background

5.3 Probabilistic Information Retrieval Models

5.4 Conclusion


Chapter 6 Language Models for Information Retrieval

6.1 Introduction

6.2 Language Models

6.3 Types of Language Models

6.4 Query Likelihood Model


Chapter 7 Classification and Clustering in Information Retrieval

7.1 Introduction

7.2 Naïve’s Bayes Classifier

7.3 Decision Tree Algorithm

7.4 Clustering and Its Association Methods

7.5 Common Distance Measures

7.6 Non-Hierarchical Methods

7.7 Partitional Clustering

7.8 Hierarchical Methods

7.9 Clustering

7.10 Problem Statement

7.11 Cardinality in Clustering

7.12 Clustering Evaluation

7.13 Classification

7.14 Classification Approaches


Chapter 8 Text Summarization

8.1 Introduction

8.2 Abstractive Summarization Approach

8.3 Extractive Text Summarization Technique

8.4 The Role of Artificial Intelligence in IR


Chapter 9 Content-based Image Retrieval

9.1 Introduction

9.2 Why Do We Need CBIR?

9.3 Image Color Feature Extraction

9.4 ISFE-Image Shape Feature Extraction

9.5 ITFE-Image Texture Feature Extraction


Chapter 10 Multimedia Information Retrieval

10.1 What Is Information Retrieval?

10.2 Architecture of MMIR

10.3 Multimedia Search Technologies

10.4 Conclusion


Chapter 11 Web Search Engine

11.1 Concept of Web Search Review

11.2 Structure of the Web

11.3 Search Engine Concept

11.4 Process of Web Crawling

11.5 Web Search—Link Analysis and Specialized Search

11.6 HITS Algorithm


Chapter 12 Relevance Feedback

12.1 Introduction

12.2 The Rocchio Algorithm for RF

12.3 Algorithm

12.4 Probabilistic RF

12.5 Assumptions for RF

12.6 When RF Does Not Work?

12.7 Pseudo/Blind RF

12.8 Indirect RF

12.9 RF on Web


Chapter 13 Question Answering

13.1 Introduction

13.2 LLC and Its Architecture


Chapter 14 XML Retrieval

14.1 Introduction

14.2 Document Object Model

14.3 XPath (XML Path Language) or XML Context

14.4 XML Retrieval Model

14.5 XML Retrieval Evaluation

14.6 Text-Centric versus Data-Centric Retrieval

14.7 IR as Relational Application



Multiple-Choice Questions

Short Answer Questions

Long Answer Questions


Answers to Multiple-Choice Questions