Information Retrieval: Models and Concepts
ISBN: 9789354246791
252 pages
Description
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
Summary
Multiple-Choice Questions
Short Answer Questions
Long Answer Questions
References
Answers to Multiple-Choice Questions
Index