Information Retrieval

Description

Information Retrieval is the science of finding specific information in a document. Many techniques are now available for Information Retrieval. This book covers the various ranking Algorithms, along with their explanation in relation to Natural Language Processing. The book covers the latest aspects of the design and implementation of information retrieval systems for gathering, indexing, searching documents and methods for evaluating different techniques.

About the Author

Dr. Madhavi Vaidya is an experienced and qualified academician and a researcher with a demonstrated history of working in the education management industry skilled in various programming languages. Dr. Madhavi has understanding and knowledge of various programming and database technologies, Data Analytics, Information Retrieval, Software Engineering and Project Management.

Yashowardhan Sowale is a senior business and technology leader. He is currently working at Capgemini as Vice President in the Insights and Data division. He heads the Enterprise Architecture center of excellence and is also India domain leader for Artificial Intelligence. He has extensive knowledge on Software Engineering, SOA, BPM, Cloud, Enterprise and Solution Architecture, Big Data, Machine Learning and Deep Learning.

Table of Contents

Book Review

Author’s Biography

Acknowledgment

Preface

Foreword

1. Boolean Retrieval

Exploring Information Retrieval Systems
Indexing in Information Retrieval
Bitwise Operations

2. Tokenization And Tolerant Retrieval

Vector Space Model
Vocabulary in Information Retrieval
Tokenizing
Stemming
Lemmatization
Concept of Wildcard Queries in IR
Stopword
Installing NLTK
Introducing NLP

3. Ranking Algorithms

Link Analysis
HITS Algorithm
Google Panda Algorithm
Personalized Search
Collaborative Filtering
Question Answering
Text Summarization
Word Cloud Generation
Keyword Extraction
Knowledge Graph
SERP – Search Engine Results Page

4. Introduction To Big Data

Introduction to Data and Big Data Concepts
Introduction to Big Data and Hadoop

5. Distributed And Parallel Computing For Big Data

Use Cases of Big Data Analytics
How Organizations are getting on Big Data Bandwagon?
Concept of Business Data Lake
New Hadoop Features for Complex Business Data Lakes
Role of Big Data in Information Retrieval
6. Hadoop Ecosystem And Big Data Processing
Introducing YARN (Yet Another Resource Negotiator)
Why YARN Based Architecture is Needed and How to Plan for It?
Failures in YARN and Causes
Hive
Apache Spark

7. Parallel And Distributed IR

Introduction to Parallel Computing
Applications of Parallel Computing
Parallel IR
Integration of IR in Object Databases
Online Public Access Catalogs (OPACs) and Their Contents
Libraries and Digital Library Projects

8. Searching The Web

Introduction to Web Search Engines
Exploring Types of Search Engines
XML Concepts

9. Introduction To Machine Learning

What is Artificial Intelligence and Machine Learning?