1300 187 187
 

Building Effective Recommender Systems

Hardcover

Published: 1st June 2012
RRP $251.99
$227.50
10%
OFF
This title is not in stock at the Booktopia Warehouse and needs to be ordered from our supplier.
Click here to read more about delivery expectations.

Recommender systems support the user with the decision-making and buying process. The explosive growth of e-commerce environments has made the issue of information overload increasingly serious. Recommender systems have proven to be a valuable means for online users to cope with the virtual information overload, and is one of the most powerful and popular tools in electronic commerce available today.Development of recommender systems is a multi-disciplinary effort involving experts from various fields such as data mining, artificial intelligence, statistics, human computer interaction, information retrieval/technology, and adaptive user interfaces. Building Effective Recommender Systems is the first comprehensive book which is dedicated entirely to the field of recommender systems. This book covers all aspects and important techniques for recommender systems, such as collaborative filtering, content based techniques, popular hybrid approaches and a detailed tutorial of recommender systems software. Building Effective Recommender Systems is designed for researchers in the fields of information technology, e-commerce, information retrieval, data mining, databases and statistics, and practitioners that work for well known corporations such as Amazon, Google, Microsoft and AT&T. This book is also suitable for advanced-level students in computer science as a secondary textbook. 

Preface
Foundation
Introduction to Recommender Systems
Useful AI Methods for Recommender Systems
Challenges in Recommender Systems
Evaluation of Recommender Systems
Techniques
Collaborative Filtering Techniques
Content-Based Techniques
Knowledge-Based Techniques
Demographic Techniques
Community Based Recommender Systems
Hybrid Techniques
PERES G++ A Workbench for Recommender Systems
Advances in Recommender Systems
Explanations in Recommender Systems
Stereotype-based Recommender Systems
Security and Trust in Recommender Systems
Elicitation of User Preferences
Ontologies and Semantic Web Technologies for Recommender Systems
Index
Table of Contents provided by Publisher. All Rights Reserved.

ISBN: 9781441900470
ISBN-10: 1441900470
Audience: Professional
Format: Hardcover
Language: English
Number Of Pages: 330
Published: 1st June 2012
Dimensions (cm): 23.5 x 15.5