Recommender Systems Handbook (Record no. 179212)

MARC details
000 -LEADER
fixed length control field 05882nam a22005895i 4500
001 - CONTROL NUMBER
control field 978-1-0716-2197-4
003 - CONTROL NUMBER IDENTIFIER
control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240423125543.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
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020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781071621974
-- 978-1-0716-2197-4
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/978-1-0716-2197-4
Source of number or code doi
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number QA76.9.D343
072 #7 - SUBJECT CATEGORY CODE
Subject category code UNF
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code UYQE
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code COM021030
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code UNF
Source thema
072 #7 - SUBJECT CATEGORY CODE
Subject category code UYQE
Source thema
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.312
Edition number 23
245 10 - TITLE STATEMENT
Title Recommender Systems Handbook
Medium [electronic resource] /
Statement of responsibility, etc edited by Francesco Ricci, Lior Rokach, Bracha Shapira.
250 ## - EDITION STATEMENT
Edition statement 3rd ed. 2022.
264 #1 -
-- New York, NY :
-- Springer US :
-- Imprint: Springer,
-- 2022.
300 ## - PHYSICAL DESCRIPTION
Extent XI, 1060 p. 129 illus., 105 illus. in color.
Other physical details online resource.
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-- computer
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-- rdamedia
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-- online resource
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-- text file
-- PDF
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505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Preface -- Introduction -- Part 1: General Recommendation Techniques -- Trust Your Neighbors: A Comprehensive Survey of Neighborhood-based Methods for Recommender Systems (Desrosiers) -- Advances in Collaborative Filtering (Koren) -- Item Recommendation from Implicit Feedback (Rendle) -- Deep Learning for Recommender Systems (Zhang) -- Context Aware Re commender Sytems : From Foundatiom to Recent Developments (Bauman) -- Semantics and Content-based Recommendations (Musto) -- Part 2: Special Recommendation Techniques -- Session-based Recommender Systems (lannoch). -- Adversarial Recommender Systems: Attack, Defense, and Advances (Di Nola) -- Group Recommender Systems: Beyond Preferance Aggregation (Masthoff) -- People-to-People Reciprocal Recommenders (Koprinska) -- Natural Language Processing for Recommender Systems (Sar-Shalom) -- Design and Evaluation of Cross-domain Recommender Systems (Cremonesi) -- Part 3: Value and Impact of Recommender Systems -- Value and Impact of Recommender Systems (Zanker) -- Evaluating Recommender Systems (Shani) -- Novelty and Diversity in Recommender Systems (Castells) -- Multistakeholder Recommender Systems (Burke) -- Fairness in Recommender Systems (Ekstrand) -- Part 4: Human Computer Interaction -- Beyond Explaining Single Item Recommendations (Tintarev) -- Personality and Recommender Systems (Tkalčič) -- Individual and Group Decision Making and Recommender Systems (Jameson) -- Part 5: Recommender Systems Applications -- Social Recommender Systems (Guy) -- Food Recommender Systems (Trattner) -- Music Recommendation Systems: Techniques, Use Cases, and Challenges (Schedl) -- Multimedia Recommender Systems: Algorithms and Challenges (Deldjoo) -- Fashion Recommender Systems (Dokoohaki).
520 ## - SUMMARY, ETC.
Summary, etc This third edition handbook describes in detail the classical methods as well as extensions and novel approaches that were more recently introduced. It consists of five parts: general recommendation techniques, special recommendation techniques, value and impact of recommender systems, human computer interaction, and applications. The first part presents the most popular and fundamental techniques currently used for building recommender systems, such as collaborative filtering, semantic-based methods, recommender systems based on implicit feedback, neural networks and context-aware methods. The second part of this handbook introduces more advanced recommendation techniques, such as session-based recommender systems, adversarial machine learning for recommender systems, group recommendation techniques, reciprocal recommenders systems, natural language techniques for recommender systems and cross-domain approaches to recommender systems. The third part covers a wideperspective to the evaluation of recommender systems with papers on methods for evaluating recommender systems, their value and impact, the multi-stakeholder perspective of recommender systems, the analysis of the fairness, novelty and diversity in recommender systems. The fourth part contains a few chapters on the human computer dimension of recommender systems, with research on the role of explanation, the user personality and how to effectively support individual and group decision with recommender systems. The last part focusses on application in several important areas, such as, food, music, fashion and multimedia recommendation. This informative third edition handbook provides a comprehensive, yet concise and convenient reference source to recommender systems for researchers and advanced-level students focused on computer science and data science. Professionals working in data analytics that are using recommendation and personalization techniques will also find this handbook a useful tool. .
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Data mining.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Information storage and retrieval systems.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Artificial intelligence.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Application software.
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Data Mining and Knowledge Discovery.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Information Storage and Retrieval.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Artificial Intelligence.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer and Information Systems Applications.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Ricci, Francesco.
Relator term editor.
Relator code edt
-- http://id.loc.gov/vocabulary/relators/edt
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Rokach, Lior.
Relator term editor.
Relator code edt
-- http://id.loc.gov/vocabulary/relators/edt
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Shapira, Bracha.
Relator term editor.
Relator code edt
-- http://id.loc.gov/vocabulary/relators/edt
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
773 0# - HOST ITEM ENTRY
Title Springer Nature eBook
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9781071621967
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9781071621981
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9781071621998
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://doi.org/10.1007/978-1-0716-2197-4">https://doi.org/10.1007/978-1-0716-2197-4</a>
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942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks-CSE-Springer

No items available.

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