JAIST Repository: 信頼値モデルによるオンラインショッピングサイトでの投稿判断支援に関する研究
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(2) 信頼値モデルによるオンラインショッピングサイトでの 投稿判断支援に関する研究. 1910252. Xue, Feifang. With the rapid development of e-commerce, consumers are keen on online shopping and publishing reviews. These reviews provide important reference information for stores, manufacturers, and potential consumers. However, the reviews may be false, and false reviews will influence the reference value to a certain extent. Therefore, it is essential to identify false e-commerce reviews. This article mainly focuses on e-commerce reviews, focusing on reviewing explicit features, implicit features, and the combinations of both. The following research work has been completed: (1) The current false reviews recognition is performed through explicit features of reviewer or review text. It does not consider the review text's semantic information, and the analysis result is not accurate enough. Therefore, an electronic business false review recognition method based on implicit semantic analysis is proposed. Based on the analysis of user behavior characteristics, this method adds semantic analysis information of review text, making it possible to identify false reviews at the semantic level of the text and improve the recognition accuracy. (2) We use the dislocation level method to evaluate the experimental results. Due to the particularity of the experimental method, it is not convenient to use traditional assessment methods. Therefore, the dislocation-level assessment method was used in this paper. (3) Finally, by providing a reference trust value, the detection proposal system can strengthen consumers' ability to identify fake reviews..
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