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Trust-based Collective View Prediction (Record no. 44833)

MARC details
000 -LEADER
fixed length control field 03904nam a22005057a 4500
001 - CONTROL NUMBER
control field sulb-eb0022741
003 - CONTROL NUMBER IDENTIFIER
control field BD-SySUS
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20160413122315.0
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 130704s2013 xxu| s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781461472025
-- 978-1-4614-7202-5
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/978-1-4614-7202-5
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 Luo, Tiejian.
Relator term author.
245 10 - TITLE STATEMENT
Title Trust-based Collective View Prediction
Medium [electronic resource] /
Statement of responsibility, etc. by Tiejian Luo, Su Chen, Guandong Xu, Jia Zhou.
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 XI, 146 p.
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
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Preface -- Introduction -- Related Work -- Collaborative Filtering -- Sentiment Analysis -- Theory Foundations -- Models, Methods and Algorithms -- Framework for Robustness Analysis -- Conclusions -- Appendix.
520 ## - SUMMARY, ETC.
Summary, etc. Collective view prediction is to judge the opinions of an active web user based on unknown elements by referring to the collective mind of the whole community. Content-based recommendation and collaborative filtering are two mainstream collective view prediction techniques. They generate predictions by analyzing the text features of the target object or the similarity of users’ past behaviors. Still, these techniques are vulnerable to the artificially-injected noise data, because they are not able to judge the reliability and credibility of the information sources. Trust-based Collective View Prediction describes new approaches for tackling this problem by utilizing users’ trust relationships from the perspectives of fundamental theory, trust-based collective view prediction algorithms and real case studies. The book consists of two main parts – a theoretical foundation and an algorithmic study. The first part will review several basic concepts and methods related to collective view prediction, such as state-of-the-art recommender systems, sentimental analysis, collective view, trust management, the Relationship of Collective View and Trustworthy, and trust in collective view prediction. In the second part, the authors present their models and algorithms based on a quantitative analysis of more than 300 thousand users’ data from popular product-reviewing websites. They also introduce two new trust-based prediction algorithms, one collaborative algorithm based on the second-order Markov random walk model, and one Bayesian fitting model for combining multiple predictors. The discussed concepts, developed algorithms, empirical results, evaluation methodologies and the robust analysis framework described in Trust-based Collective View Prediction will not only provide valuable insights and findings to related research communities and peers, but also showcase the great potential to encourage industries and business partners to integrate these techniques into new applications.
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).
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Chen, Su.
Relator term author.
Personal name Xu, Guandong.
Relator term author.
Personal name Zhou, Jia.
Relator term author.
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 9781461472018
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="http://dx.doi.org/10.1007/978-1-4614-7202-5">http://dx.doi.org/10.1007/978-1-4614-7202-5</a>
912 ## -
-- ZDB-2-SCS
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme
Koha item type

No items available.