The Resource Recommender systems handbook, Francesco Ricci, Lior Rokach, Bracha Shapira, editors

Recommender systems handbook, Francesco Ricci, Lior Rokach, Bracha Shapira, editors

Label
Recommender systems handbook
Title
Recommender systems handbook
Statement of responsibility
Francesco Ricci, Lior Rokach, Bracha Shapira, editors
Contributor
Editor
Subject
Genre
Language
eng
Summary
This second edition of a well-received text, with 20 new chapters, presents a coherent and unified repository of recommender systemsĺl major concepts, theories, methodologies, trends, and challenges. A variety of real-world applications and detailed case studies are included. In addition to wholesale revision of the existing chapters, this edition includes new topics including: decision making and recommender systems, reciprocal recommender systems, recommender systems in social networks, mobile recommender systems, explanations for recommender systems, music recommender systems, cross-domain recommendations, privacy in recommender systems, and semantic-based recommender systems. This multi-disciplinary handbook involves world-wide experts from diverse fields such as artificial intelligence, human-computer interaction, information retrieval, data mining, mathematics, statistics, adaptive user interfaces, decision support systems, psychology, marketing, and consumer behavior. Theoreticians and practitioners from these fields will find this reference to be an invaluable source of ideas, methods and techniques for developing more efficient, cost-effective and accurate recommender systems
Cataloging source
N$T
Dewey number
006.33
Illustrations
illustrations
Index
index present
LC call number
QA76.9.I58
Literary form
non fiction
Nature of contents
  • dictionaries
  • bibliography
http://library.link/vocab/relatedWorkOrContributorName
  • Ricci, Francesco
  • Rokach, Lior
  • Shapira, Bracha
http://library.link/vocab/subjectName
  • Recommender systems (Information filtering)
  • COMPUTERS
  • Recommender systems (Information filtering)
  • Computer Science
  • Information Storage and Retrieval
  • Artificial Intelligence (incl. Robotics)
Label
Recommender systems handbook, Francesco Ricci, Lior Rokach, Bracha Shapira, editors
Link
https://ezproxy.lib.ou.edu/login?url=http://link.springer.com/10.1007/978-1-4899-7637-6
Instantiates
Publication
Copyright
Antecedent source
unknown
Bibliography note
Includes bibliographical references and index
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
Recommender Systems: Introduction and Challenges -- A Comprehensive Survey of Neighborhood-based Recommendation Methods -- Advances in Collaborative Filtering -- Semantics-aware Content-based Recommender Systems -- Constraint-based Recommender Systems -- Context-Aware Recommender Systems -- Data Mining Methods for Recommender Systems -- Evaluating Recommender Systems -- Evaluating Recommender Systems with User Experiments -- Explaining Recommendations: Design and Evaluation -- Recommender Systems in Industry: A Netflix Case Study -- Panorama of Recommender Systems to Support Learning -- Music Recommender Systems -- The Anatomy of Mobile Location-Based Recommender Systems -- Social Recommender Systems -- People-to-People Reciprocal Recommenders -- Collaboration, Reputation and Recommender Systems in Social Web Search -- Human Decision Making and Recommender Systems -- Privacy Aspects of Recommender Systems -- Source Factors in Recommender System Credibility Evaluation -- Personality and Recommender Systems -- Group Recommender Systems: Aggregation, Satisfaction and Group Attributes -- Aggregation Functions for Recommender Systems -- Active Learning in Recommender Systems -- Multi-Criteria Recommender Systems -- Novelty and Diversity in Recommender Systems -- Cross-domain Recommender Systems -- Robust Collaborative Recommendation
Dimensions
unknown
Edition
Second edition.
Extent
1 online resource (xvii, 1003 pages)
File format
unknown
Form of item
online
Isbn
9781489976369
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Note
SpringerLink
Other control number
10.1007/978-1-4899-7637-6
Other physical details
illustrations
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
System control number
  • (OCoLC)929952078
  • (OCoLC)ocn929952078
Label
Recommender systems handbook, Francesco Ricci, Lior Rokach, Bracha Shapira, editors
Link
https://ezproxy.lib.ou.edu/login?url=http://link.springer.com/10.1007/978-1-4899-7637-6
Publication
Copyright
Antecedent source
unknown
Bibliography note
Includes bibliographical references and index
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
Recommender Systems: Introduction and Challenges -- A Comprehensive Survey of Neighborhood-based Recommendation Methods -- Advances in Collaborative Filtering -- Semantics-aware Content-based Recommender Systems -- Constraint-based Recommender Systems -- Context-Aware Recommender Systems -- Data Mining Methods for Recommender Systems -- Evaluating Recommender Systems -- Evaluating Recommender Systems with User Experiments -- Explaining Recommendations: Design and Evaluation -- Recommender Systems in Industry: A Netflix Case Study -- Panorama of Recommender Systems to Support Learning -- Music Recommender Systems -- The Anatomy of Mobile Location-Based Recommender Systems -- Social Recommender Systems -- People-to-People Reciprocal Recommenders -- Collaboration, Reputation and Recommender Systems in Social Web Search -- Human Decision Making and Recommender Systems -- Privacy Aspects of Recommender Systems -- Source Factors in Recommender System Credibility Evaluation -- Personality and Recommender Systems -- Group Recommender Systems: Aggregation, Satisfaction and Group Attributes -- Aggregation Functions for Recommender Systems -- Active Learning in Recommender Systems -- Multi-Criteria Recommender Systems -- Novelty and Diversity in Recommender Systems -- Cross-domain Recommender Systems -- Robust Collaborative Recommendation
Dimensions
unknown
Edition
Second edition.
Extent
1 online resource (xvii, 1003 pages)
File format
unknown
Form of item
online
Isbn
9781489976369
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Note
SpringerLink
Other control number
10.1007/978-1-4899-7637-6
Other physical details
illustrations
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
System control number
  • (OCoLC)929952078
  • (OCoLC)ocn929952078

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