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- W2978883167 abstract "In recent years, websites that incorporate user reviews, such as Amazon, IMDB and YELP, have become exceedingly popular. As an important factor affecting users purchasing behavior, review information has been becoming increasingly important, and accordingly, the reliability of review information becomes an important issue. This paper proposes a method to more accurately detect the appearance period of spam reviews and to identify the spam reviews by verifying the consistency of review information among multiple review sites. Evaluation experiments were conducted to show the accuracy of the detection results, and compared the newly proposed method with our previously proposed method." @default.
- W2978883167 created "2019-10-10" @default.
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- W2978883167 date "2019-08-01" @default.
- W2978883167 modified "2023-09-25" @default.
- W2978883167 title "A Spam Review Detection Method by Verifying Consistency among Multiple Review Sites" @default.
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- W2978883167 doi "https://doi.org/10.1109/hpcc/smartcity/dss.2019.00396" @default.
- W2978883167 hasPublicationYear "2019" @default.
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