Tiejian (54 results)
- Softcover
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- Softcover
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- Softcover
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- Softcover
Seller: Ria Christie Collections, Uxbridge, United KingdomRia Christie Collections
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- Hardcover
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- Softcover
Seller: Ria Christie Collections, Uxbridge, United KingdomRia Christie Collections
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- Hardcover
Seller: Ria Christie Collections, Uxbridge, United KingdomRia Christie Collections
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- Hardcover
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- Hardcover
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- Softcover
Seller: California Books, Miami, FL, U.S.A.California Books
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- Softcover
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- Softcover
Seller: California Books, Miami, FL, U.S.A.California Books
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- Hardcover
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- Hardcover
Seller: Books Puddle, New York, NY, U.S.A.Books Puddle
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- Hardcover
Seller: Revaluation Books, Exeter, United KingdomRevaluation Books
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More images- Softcover
Seller: preigu, Osnabrück, Germanypreigu
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£ 83.43
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Taschenbuch. Condition: Neu. Trust-based Collective View Prediction | Tiejian Luo (u. a.) | Taschenbuch | xi | Englisch | 2015 | Springer | EAN 9781489992000 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
- Hardcover
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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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 pre…diction 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.
- Softcover
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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£ 98.78
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Taschenbuch. 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 v…iew 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.
- Hardcover
Seller: Buchpark, Trebbin, GermanyBuchpark
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£ 61.94
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Condition: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | 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 v…iew 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.
- Softcover
Seller: Books Puddle, New York, NY, U.S.A.Books Puddle
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£ 152.38
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Condition: New. pp. 146.
- Hardcover
Seller: Buchpark, Trebbin, GermanyBuchpark
Contact seller5-star sellerCondition: Used
£ 63.79
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Condition: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | 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 coll…ective 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.
- Softcover
Seller: PBShop.store UK, Fairford, GLOS, United KingdomPBShop.store UK
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PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.
- Softcover
Seller: PBShop.store UK, Fairford, GLOS, United KingdomPBShop.store UK
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- Softcover
Seller: PBShop.store UK, Fairford, GLOS, United KingdomPBShop.store UK
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- Softcover
Seller: Mispah books, Redhill, SURRE, United KingdomMispah books
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£ 163.00
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- Softcover
Seller: Ria Christie Collections, Uxbridge, United KingdomRia Christie Collections
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- Softcover
Seller: Ria Christie Collections, Uxbridge, United KingdomRia Christie Collections
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- Softcover
Seller: Ria Christie Collections, Uxbridge, United KingdomRia Christie Collections
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- Softcover
- Print on Demand
Seller: Majestic Books, Hounslow, United KingdomMajestic Books
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£ 72.18
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- Softcover
- Print on Demand
Seller: Books Puddle, New York, NY, U.S.A.Books Puddle
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