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Trust for Intelligent Recommendation (Record no. 44751)

MARC details
000 -LEADER
fixed length control field 04087nam a22004937a 4500
001 - CONTROL NUMBER
control field sulb-eb0022659
003 - CONTROL NUMBER IDENTIFIER
control field BD-SySUS
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20160413122311.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr nn 008mamaa
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 130331s2013 xxu| s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781461468950
-- 978-1-4614-6895-0
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/978-1-4614-6895-0
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
Subject category code UYQE
Source bicssc
Subject category code COM021030
Source bisacsh
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.312
Edition number 23
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Bhuiyan, Touhid.
Relator term author.
245 10 - TITLE STATEMENT
Title Trust for Intelligent Recommendation
Medium [electronic resource] /
Statement of responsibility, etc. by Touhid Bhuiyan.
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture New York, NY :
Name of producer, publisher, distributor, manufacturer Springer New York :
-- Imprint: Springer,
Date of production, publication, distribution, manufacture, or copyright notice 2013.
300 ## - PHYSICAL DESCRIPTION
Extent XIV, 119 p. 34 illus.
Other physical details online resource.
336 ## - CONTENT TYPE
Content type term text
Content type code txt
Source rdacontent
337 ## - MEDIA TYPE
Media type term computer
Media type code c
Source rdamedia
338 ## - CARRIER TYPE
Carrier type term online resource
Carrier type code cr
Source rdacarrier
347 ## - DIGITAL FILE CHARACTERISTICS
File type text file
Encoding format PDF
Source rda
490 1# - SERIES STATEMENT
Series statement SpringerBriefs in Electrical and Computer Engineering,
International Standard Serial Number 2191-8112
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Introduction -- Literature Review -- Trust Inferences using Subjective Logic -- Online Survey on Trust and Interest Similarity -- SimTrust: The Algorithm for Similarity-based Trust Network Generation -- Experiments and Evaluation -- Conclusions -- Appendix A: Sample Survey Questions -- Appendix B:  Glossary of Terms and Abbreviations -- Appendix C:  Combining Trust & Reputation Management.
520 ## - SUMMARY, ETC.
Summary, etc. Recommender systems are one of the recent inventions to deal with the ever-growing information overload in relation to the selection of goods and services in a global economy. Collaborative Filtering (CF) is one of the most popular techniques in recommender systems. The CF recommends items to a target user based on the preferences of a set of similar users known as the neighbors, generated from a database made up of the preferences of past users. In the absence of these ratings, trust between the users could be used to choose the neighbor for recommendation making. Better recommendations can be achieved using an inferred trust network which mimics the real world “friend of a friend” recommendations. To extend the boundaries of the neighbor, an effective trust inference technique is required. This book proposes a trust interference technique called Directed Series Parallel Graph (DSPG) that has empirically outperformed other popular trust inference algorithms, such as TidalTrust and MoleTrust. For times when reliable explicit trust data is not available, this book outlines a new method called SimTrust for developing trust networks based on a user’s interest similarity. To identify the interest similarity, a user’s personalized tagging information is used. However, particular emphasis is given in what resources the user chooses to tag, rather than the text of the tag applied. The commonalities of the resources being tagged by the users can be used to form the neighbors used in the automated recommender system. Through a series of case studies and empirical results, this book highlights the effectiveness of this tag-similarity based method over the traditional collaborative filtering approach, which typically uses rating data. Trust for Intelligent Recommendation is intended for practitioners as a reference guide for developing improved, trust-based recommender systems. Researchers in a related field will also find this book valuable.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer science.
Topical term or geographic name as entry element Data mining.
Topical term or geographic name as entry element Artificial intelligence.
Topical term or geographic name as entry element Computer Science.
Topical term or geographic name as entry element Data Mining and Knowledge Discovery.
Topical term or geographic name as entry element Information Systems Applications (incl. Internet).
Topical term or geographic name as entry element Artificial Intelligence (incl. Robotics).
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
773 0# - HOST ITEM ENTRY
Title Springer eBooks
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Relationship information Printed edition:
International Standard Book Number 9781461468943
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title SpringerBriefs in Electrical and Computer Engineering,
International Standard Serial Number 2191-8112
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="http://dx.doi.org/10.1007/978-1-4614-6895-0">http://dx.doi.org/10.1007/978-1-4614-6895-0</a>
912 ## -
-- ZDB-2-SCS
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme
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No items available.