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Qinyu Hu, Xiaomei Zhang, Fangqi Li, Zhushou Tang and Shilin Wang
Application marketplaces collect ratings and reviews from users to provide references for other consumers. Many crowdturfing activities abuse user reviews to manipulate the reputation of an app and mislead other consumers. To understand and improve the e...
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Soroush Ojagh, Mohammad Reza Malek and Sara Saeedi
Providing recommendations in cold start situations is one of the most challenging problems for collaborative filtering based recommender systems (RSs). Although user social context information has largely contributed to the cold start problem, most of th...
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Alvaro Parres-Peredo, Ivan Piza-Davila and Francisco Cervantes
Anomaly-based intrusion detection systems use profiles to characterize expected behavior of network users. Most of these systems characterize the entire network traffic within a single profile. This work proposes a user-level anomaly-based intrusion dete...
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Konstantinos Georgiou, Christos Makris and Georgios Pispirigos
Nowadays, the amount of digitally available information has tremendously grown, with real-world data graphs outreaching the millions or even billions of vertices. Hence, community detection, where groups of vertices are formed according to a well-defined...
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Zihe Zhou and Bo Tian
The text data of the social network platforms take the form of short texts, and the massive text data have high-dimensional and sparse characteristics, which does not make the traditional clustering algorithm perform well. In this paper, a new community ...
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