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Trust evaluation of multimedia documents based on extended provenance model in social semantic web

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Abstract

Recently, the importance of social semantic web, which is a combination of the semantic web and the social web, has been increasing with active data creation and sharing through the Web. In this paper, we proposes a provenance based trust evaluation scheme of multimedia documents by extending the PROV data model in social semantic web. The proposed scheme extends the PROV data model of W3C to manage the provenance and evaluate the trust of multimedia documents in a social semantic web environment. The trust of multimedia documents is evaluated by considering the agent trust, source document trust, and reputation score of current document. The evaluated trust is managed as provenance information, and when users request a query, the query results are generated by considering trust. To verify the validity of the proposed scheme, the trust is compared and evaluated using SPARQL queries.

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Acknowledgments

This research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Education(2015R1D1A3A01015962), by the MSIT(Ministry of Science, ICT), Korea, under the ITRC (Information Technology Research Center) support program (IITP-2018-2013-1-00881) supervised by the IITP(Institute for Information & communication Technology Promotion), by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (No. 2016R1A2B3007527), and by Next-Generation Information Computing Development Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT (No. NRF-2017M3C4A7069432).

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  1. School of Information and Communication Engineering,, Chungbuk National University, Chungdae-ro 1, Seowon-Gu, Cheongju, Chungbuk, 28644, South Korea

    Kyoungsoo Bok, Sangwon Yoon & Jaesoo Yoo

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  1. Kyoungsoo Bok
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Correspondence to Jaesoo Yoo.

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Bok, K., Yoon, S. & Yoo, J. Trust evaluation of multimedia documents based on extended provenance model in social semantic web. Multimed Tools Appl 78, 28681–28702 (2019). https://doi.org/10.1007/s11042-018-6243-7

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