The dataset contains constructed multi-modal features (visual and textual), pseudo-labels (on heritage values and attributes), and graph structures (with temporal, social, and spatial links) constructed
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This webgraph is a page-page graph of verified Facebook sites. Nodes represent official Facebook pages while the links are mutual likes between sites. This graph was collected through the Facebook Graph API in November 2017 and restricted to pages from 4 categories which are defined by Facebook. This web graph is a page-page graph of verified Facebook sites. Nodes represent official Facebook pages while the links are mutual likes between sites. This graph was collected through the Facebook Graph API in November 2017 and restricted to pages from 4 categories that are defined by Facebook.
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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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The Reddit dataset is a graph dataset from Reddit posts made in the month of September, 2014. The node label in this case is the community, or “subreddit”, that a post belongs to. 50 large communities have been sampled to build a post-to-post graph, connecting posts if the same user comments on
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…Although existing space function classifiers use space adjacency or connectivity graphs as input, the application of Graph Deep Learning (GDL) to space layout element classification has not been extensively To bridge this gap, we introduce a dataset named SAGC-A68, which comprises access graphs automatically generated from 68 digital 3D models of space layouts of apartment buildings designed or built between Each access graph contains nodes representing spaces and space elements and edges representing the connection between them.
…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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…We here abstract the problem into a new benchmark for node classification in a geo-referenced graph. Solving it requires learning the spatial layout of the organ including symmetries.
MuMiN is a misinformation graph dataset containing rich social media data (tweets, replies, users, images, articles, hashtags), spanning 21 million tweets belonging to 26 thousand Twitter threads, each
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