Amazon-Fraud is a multi-relational graph dataset built upon the Amazon review dataset, which can be used in evaluating graph-based node classification, fraud detection, and anomaly detection models. Class=1)| |-------|--------| | 11,944 | 9.5 | | Relation | # Edges | |--------|--------| | U-P-U | 175,608 | | U-S-U | 3,566,479 | | U-V-U | 1,036,737 | | All | 4,398,392 | Graph We take users as nodes in the graph and design three relations: 1) U-P-U: it connects users reviewing at least one same product; 2) U-S-V: it connects users having at least one same star rating within
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Yelp-Fraud is a multi-relational graph dataset built upon the Yelp spam review dataset, which can be used in evaluating graph-based node classification, fraud detection, and anomaly detection models. Class=1) | |-------|--------| | 45,954 | 14.5 | | Relation | # Edges | |--------|--------| | R-U-R | 49,315 | | R-T-R | 573,616 | | R-S-R | 3,402,743 | | All | 3,846,979 | Graph Based on previous studies which show that opinion fraudsters have connections in user, product, review text, and time, we take reviews as nodes in the graph and design three relations: 1) R-U-R: it connects
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…We construct a multi-relation graph based on the supplier, customer, shareholder, and financial information disclosed in the financial statements of Chinese companies.
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