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Trust-based collective view prediction

著者: Tiejian Luo; Su Chen; Guandong Xu; Jia Zhou
出版: New York, NY : Springer, ©2013.
エディション/フォーマット:   電子書籍 : Document : Englishすべてのエディションとフォーマットを見る
データベース:WorldCat
概要:
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  続きを読む
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ジャンル/形式: Electronic books
Ebook
資料の種類: Document, インターネット資料
ドキュメントの種類: インターネットリソース, コンピューターファイル
すべての著者/寄与者: Tiejian Luo; Su Chen; Guandong Xu; Jia Zhou
ISBN: 9781461472025 1461472024 1461472016 9781461472018
OCLC No.: 852689603
物理形態: 1 online resource
コンテンツ: Preface --
Introduction --
Related Work --
Collaborative Filtering --
Sentiment Analysis --
Theory Foundations --
Models, Methods and Algorithms --
Framework for Robustness Analysis --
Conclusions --
Appendix.
責任者: Tiejian Luo, Su Chen, Guandong Xu, Jia Zhou.
その他の情報:

概要:

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.

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