Items related to Trust-based Collective View Prediction
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.
"synopsis" may belong to another edition of this title.
- PublisherSpringer
- Publication date2013
- ISBN 10 1461472016
- ISBN 13 9781461472018
- BindingHardcover
- Number of pages157
Buy New
Learn more about this copy
US$ 106.28
Shipping:
FREE
Within U.S.A.
Top Search Results from the AbeBooks Marketplace
Seller Image
Trust-based Collective View Prediction by Luo, Tiejian, Chen, Su, Xu, Guandong, Zhou, Jia [Hardcover ]
Seller:
Rating
Book Description Hardcover. Condition: new. Seller Inventory # 9781461472018
Buy New
US$ 106.28
Convert currency
Stock Image
Trust-based Collective View Prediction
Published by
Springer
(2013)
ISBN 10: 1461472016
ISBN 13: 9781461472018
New
Hardcover
Quantity: > 20
Seller:
Rating
Book Description Condition: New. Seller Inventory # ABLIING23Mar2716030037154
Buy New
US$ 116.18
Convert currency
Stock Image
Trust-based Collective View Prediction
Published by
Springer
(2013)
ISBN 10: 1461472016
ISBN 13: 9781461472018
New
Hardcover
Quantity: > 20
Seller:
Rating
Book Description Condition: New. PRINT ON DEMAND Book; New; Fast Shipping from the UK. No. book. Seller Inventory # ria9781461472018_lsuk
Buy New
US$ 124.43
Convert currency
Seller Image
Trust-based Collective View Prediction
Published by
Springer New York Jun 2013
(2013)
ISBN 10: 1461472016
ISBN 13: 9781461472018
New
Hardcover
Quantity: 2
Seller:
Rating
Book Description Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 160 pp. Englisch. Seller Inventory # 9781461472018
Buy New
US$ 118.68
Convert currency
Seller Image
Trust-based Collective View Prediction
Published by
Springer New York
(2013)
ISBN 10: 1461472016
ISBN 13: 9781461472018
New
Hardcover
Quantity: > 20
Seller:
Rating
Book Description Gebunden. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Outlines recent theoretical advances and algorithmic innovations conducted in trust-based collective view predictionAnalyzes the existing vulnerabilities of the content-based recommendation and collaborative filtering techniques, and proposes new,. Seller Inventory # 4199301
Buy New
US$ 102.35
Convert currency
Seller Image
Trust-based Collective View Prediction
Published by
Springer New York
(2013)
ISBN 10: 1461472016
ISBN 13: 9781461472018
New
Hardcover
Quantity: 1
Seller:
Rating
Book Description Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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 tointegrate these techniques into new applications. Seller Inventory # 9781461472018
Buy New
US$ 121.37
Convert currency
Stock Image
Trust-based Collective View Prediction
Published by
Springer-Verlag New York Inc.
(2013)
ISBN 10: 1461472016
ISBN 13: 9781461472018
New
Hardcover
Quantity: > 20
Seller:
Rating
Book Description Hardback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days. Seller Inventory # C9781461472018
Buy New
US$ 179.79
Convert currency