Experiment and Evaluation in Information Retrieval Models

K. Latha

July 27, 2017 by Chapman and Hall/CRC
Reference - 282 Pages - 52 B/W Illustrations
ISBN 9781138032316 - CAT# K30702

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Features

The focus of this book is on recent topics in Information Retrieval research, which are typically not (yet) covered in any textbooks of Information Retrieval & Data Mining.

The focus topics include: search in social media, making use of semantic annotations, learning to rank documents based on many features and Evaluating IR systems offline and online

Covers advanced topics on information retrieval: Advanced methods for information retrieval (IR), clustering and classification for IR, Indexing methods for scalable retrieval, personalizing of results and Statistics for IR.

The applications motivates the readers to actively apply principles, techniques and methods from the information retrieval domain on advanced applications

It helps the reader to be able to carry out advanced techniques for retrieval of various information types

Summary

Experiment and Evaluation in Information Retrieval Models explores different algorithms for the application of evolutionary computation to the field of information retrieval (IR). As well as examining existing approaches to resolving some of the problems in this field, results obtained by researchers are critically evaluated in order to give readers a clear view of the topic.

In addition, this book covers Algorithmic Solutions to the Problems in Advanced IR Concepts, including Feature Selection for Document Ranking, web page classification and recommendation, Facet Generation for Document Retrieval, Duplication Detection and seeker satisfaction in question answering community Portals.

Written with students and researchers in the field on information retrieval in mind, this book is also a useful tool for researchers in the natural and social sciences interested in the latest developments in the fast-moving subject area.

Key features:

Focusing on recent topics in Information Retrieval research, Experiment and Evaluation in Information Retrieval Models explores the following topics in detail:

  • Searching in social media
  • Using semantic annotations
  • Ranking documents based on Facets 
  • Evaluating IR systems offline and online
  • The role of evolutionary computation in IR
  • Document and term clustering,
  • Image retrieval
  • Design of user profiles for IR
  • Web page classification and recommendation
  • Relevance feedback approach for Document and image retrieval