Mechanizing Social Trust-Aware Recommenders with T-index Augmented Trustworthiness

Soude Fazeli, Alireza Zarghami, Nima Dokoohaki, Mihhail Matskin

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    5 Citations (Scopus)
    14 Downloads (Pure)

    Abstract

    Social Networks have dominated growth and popularity of the Web to an extent which has never been witnessed before. Such popularity puts forward issue of trust to the participants of Social Networks. Collaborative Filtering Recommenders have been among many systems which have begun taking full advantage of Social Trust phenomena for generating more accurate predictions. For analyzing the evolution of constructed networks of trust, we utilize Collaborative Filtering enhanced with T-index as an estimate of a user’s trustworthiness to identify and select neighbors in an effective manner. Our empirical evaluation demonstrates how T-index improves the Trust Network structure by generating connections to more trustworthy users. We also show that exploiting T-index results in better prediction accuracy and coverage of recommendations collected along few edges that connect users on a network.
    Original languageEnglish
    Title of host publicationTrust, Privacy and Security in Digital Business
    Subtitle of host publication7th International Conference, TrustBus 2010, Bilbao, Spain, August 30-31, 2010. Proceedings
    EditorsSokratis Katsikas, Javier Lopez, Miguel Soriano
    Place of PublicationBerlin, Heidelberg
    PublisherSpringer
    Pages202-213
    Number of pages12
    ISBN (Electronic)978-3-642-15152-1
    ISBN (Print)978-3-642-15151-4
    DOIs
    Publication statusPublished - 31 Aug 2010
    Event7th International Conference on Trust, Privacy and Security in Digital Business, TrustBus 2010 - Bilbao, Spain
    Duration: 30 Aug 201031 Aug 2010
    Conference number: 7

    Publication series

    NameLecture Notes in Computer Science
    PublisherSpringer
    Volume6264
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Conference

    Conference7th International Conference on Trust, Privacy and Security in Digital Business, TrustBus 2010
    Abbreviated titleTrustBus
    CountrySpain
    CityBilbao
    Period30/08/1031/08/10

    Fingerprint

    Collaborative filtering

    Keywords

    • METIS-271089
    • IR-73927
    • Recommendation
    • Trust Networks
    • EWI-18644
    • Social Trust
    • Social Networks
    • Ontological modeling
    • Performance
    • Collaborative Filtering

    Cite this

    Fazeli, S., Zarghami, A., Dokoohaki, N., & Matskin, M. (2010). Mechanizing Social Trust-Aware Recommenders with T-index Augmented Trustworthiness. In S. Katsikas, J. Lopez, & M. Soriano (Eds.), Trust, Privacy and Security in Digital Business: 7th International Conference, TrustBus 2010, Bilbao, Spain, August 30-31, 2010. Proceedings (pp. 202-213). (Lecture Notes in Computer Science; Vol. 6264). Berlin, Heidelberg: Springer. https://doi.org/10.1007/978-3-642-15152-1_18
    Fazeli, Soude ; Zarghami, Alireza ; Dokoohaki, Nima ; Matskin, Mihhail. / Mechanizing Social Trust-Aware Recommenders with T-index Augmented Trustworthiness. Trust, Privacy and Security in Digital Business: 7th International Conference, TrustBus 2010, Bilbao, Spain, August 30-31, 2010. Proceedings. editor / Sokratis Katsikas ; Javier Lopez ; Miguel Soriano. Berlin, Heidelberg : Springer, 2010. pp. 202-213 (Lecture Notes in Computer Science).
    @inproceedings{d280e8f3197a45f8815ef323f11eaf74,
    title = "Mechanizing Social Trust-Aware Recommenders with T-index Augmented Trustworthiness",
    abstract = "Social Networks have dominated growth and popularity of the Web to an extent which has never been witnessed before. Such popularity puts forward issue of trust to the participants of Social Networks. Collaborative Filtering Recommenders have been among many systems which have begun taking full advantage of Social Trust phenomena for generating more accurate predictions. For analyzing the evolution of constructed networks of trust, we utilize Collaborative Filtering enhanced with T-index as an estimate of a user’s trustworthiness to identify and select neighbors in an effective manner. Our empirical evaluation demonstrates how T-index improves the Trust Network structure by generating connections to more trustworthy users. We also show that exploiting T-index results in better prediction accuracy and coverage of recommendations collected along few edges that connect users on a network.",
    keywords = "METIS-271089, IR-73927, Recommendation, Trust Networks, EWI-18644, Social Trust, Social Networks, Ontological modeling, Performance, Collaborative Filtering",
    author = "Soude Fazeli and Alireza Zarghami and Nima Dokoohaki and Mihhail Matskin",
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    Fazeli, S, Zarghami, A, Dokoohaki, N & Matskin, M 2010, Mechanizing Social Trust-Aware Recommenders with T-index Augmented Trustworthiness. in S Katsikas, J Lopez & M Soriano (eds), Trust, Privacy and Security in Digital Business: 7th International Conference, TrustBus 2010, Bilbao, Spain, August 30-31, 2010. Proceedings. Lecture Notes in Computer Science, vol. 6264, Springer, Berlin, Heidelberg, pp. 202-213, 7th International Conference on Trust, Privacy and Security in Digital Business, TrustBus 2010, Bilbao, Spain, 30/08/10. https://doi.org/10.1007/978-3-642-15152-1_18

    Mechanizing Social Trust-Aware Recommenders with T-index Augmented Trustworthiness. / Fazeli, Soude; Zarghami, Alireza; Dokoohaki, Nima; Matskin, Mihhail.

    Trust, Privacy and Security in Digital Business: 7th International Conference, TrustBus 2010, Bilbao, Spain, August 30-31, 2010. Proceedings. ed. / Sokratis Katsikas; Javier Lopez; Miguel Soriano. Berlin, Heidelberg : Springer, 2010. p. 202-213 (Lecture Notes in Computer Science; Vol. 6264).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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    AU - Matskin, Mihhail

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    PY - 2010/8/31

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    AB - Social Networks have dominated growth and popularity of the Web to an extent which has never been witnessed before. Such popularity puts forward issue of trust to the participants of Social Networks. Collaborative Filtering Recommenders have been among many systems which have begun taking full advantage of Social Trust phenomena for generating more accurate predictions. For analyzing the evolution of constructed networks of trust, we utilize Collaborative Filtering enhanced with T-index as an estimate of a user’s trustworthiness to identify and select neighbors in an effective manner. Our empirical evaluation demonstrates how T-index improves the Trust Network structure by generating connections to more trustworthy users. We also show that exploiting T-index results in better prediction accuracy and coverage of recommendations collected along few edges that connect users on a network.

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    Fazeli S, Zarghami A, Dokoohaki N, Matskin M. Mechanizing Social Trust-Aware Recommenders with T-index Augmented Trustworthiness. In Katsikas S, Lopez J, Soriano M, editors, Trust, Privacy and Security in Digital Business: 7th International Conference, TrustBus 2010, Bilbao, Spain, August 30-31, 2010. Proceedings. Berlin, Heidelberg: Springer. 2010. p. 202-213. (Lecture Notes in Computer Science). https://doi.org/10.1007/978-3-642-15152-1_18