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  • 标题:A Trust and Reputation Model for Quality Assessment of Online Content
  • 本地全文:下载
  • 作者:Yousef Elsheikh
  • 期刊名称:International Journal of Advanced Computer Science and Applications(IJACSA)
  • 印刷版ISSN:2158-107X
  • 电子版ISSN:2156-5570
  • 出版年度:2017
  • 卷号:8
  • 期号:3
  • DOI:10.14569/IJACSA.2017.080309
  • 出版社:Science and Information Society (SAI)
  • 摘要:In recent years, online transactions have become more prevalent than it was. This means that the number of online users to perform such transactions keeps growing, causing an increase in the level of expectations for them. One of those expectations is to enable them to get a better understanding of such transactions before going ahead with it. Consequently, trust and reputation models represent an important milestone to support those users to make their own decisions to facilitate online transactions. Many of the common trust and reputation models used primitive methods to calculate the reputation of online content. These methods are usually inaccurate when there is a divergence in rating. In addition, the lack of predictability through the latter ratings in emerging trends. Others use a probabilistic model or the so-called weighted average, which usually focusing on a single dimension for online user ratings. Even those models that combine multiple dimensions of user ratings are usually not representative on the one hand, and on the other hand are with heterogeneous weights. This paper fills this gap by proposing a model to assess the trust and reputation of online content, relying on three factors namely user behavior, user reliability, and user tendency with homogeneous weights of interest to the user on the Internet. These homogenous weights will be used to measure the reputation of any online content. The proposed model has been validated and compared with some other well-known models, and showed a significant improvement in terms of the Mean Absolute Error (MAE). The proposed model is also good with sparse and dense datasets.
  • 关键词:thesai; IJACSA Volume 8 Issue 3; Online content; Quality assessment; Trust and reputation model; User behaviour; User reliability; user tendency
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