False review detection method based on double cycle graph
A detection method and double-loop technology, applied in the field of network security, can solve the problems of poor filtering effect and low credibility of the initial value of confidence.
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[0093] The three Yelp data sets used in the experiment example are:
[0094] YelpChi dataset, containing 67395 reviews, 38063 users and 201 stores;
[0095] YelpNYC dataset, containing 359,052 reviews, 160,225 users and 923 stores;
[0096] The YelpZip dataset contains 608,598 reviews, 260,277 users, and 5,044 stores.
[0097] Using the above false review detection method to test three Yelp data sets, the test results are:
[0098] In the YelpChi dataset, fake users account for about 20.33% of the total number of users, and fake reviews account for about 13.23% of the total number of reviews; in the YelpNYC dataset, fake users account for about 17.79% of the total number of users, and fake reviews account for about 10.27% of the total number of reviews; fake users in the YelpZip dataset Accounting for about 23.91% of the total number of users, fake reviews accounted for about 13.22% of the total number of reviews.
[0099] It can be seen that the false comment detection met...
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