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Bücher Englische Bücher Wissen & Bildung Naturwissenschaft, Medizin, Informatik, Technik Informatik & EDV Informatik Trust-based Collective View Prediction
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Trust-based Collective View Prediction
Jia Zhou (Gebundene Ausgabe, Englisch)
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Beschreibung
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. Dieses Produkt haben wir gerade leider nicht auf Lager.
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Technische Daten
Erscheinungsdatum
28.06.2013
Sprache
Englisch
EAN
9781461472018
Herausgeber
Springer US
Sonderedition
Nein
Autor
Jia Zhou
Seitenanzahl
146
Auflage
1
Einbandart
Gebundene Ausgabe
Schlagwörter
collective view, data mining, recommender systems, trust management, trust network
Thema-Inhalt
UNF - Data Mining
UYQE - Wissensbasierte Systeme, Expertensysteme
UX - Angewandte Informatik
UYQ - Künstliche Intelligenz
Höhe
235 mm
Breite
15.5 cm
Hersteller: Springer Nature Customer Service Center GmbH, Europaplatz 3, Heidelberg, Deutschland, 69115, ProductSafety@springernature.com
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