GRUEL
发表于 2025-3-25 05:58:50
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N斯巴达人
发表于 2025-3-25 08:30:36
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lymphedema
发表于 2025-3-25 15:01:44
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繁殖
发表于 2025-3-25 16:31:11
Boost Clickbait Detection Based on User Behavior Analysiscrease click-through rate, but decrease user experience. Thus, it is important to identify the articles with a misleading title and block them for specific users. Existing methods just consider text features, which hardly produce a satisfactory result. User behavior is useful in clickbait detection.
含糊其辞
发表于 2025-3-25 20:46:03
A Novel Hybrid Friends Recommendation Framework for Twitter recently in the area of social networks analysis as users would like to follow people who have similar interests to them. We use Twitter as a case study and propose a novel hybrid friends recommendation framework that is not only based on friends relationship but also users’ location information, w
匍匐前进
发表于 2025-3-26 03:21:23
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superfluous
发表于 2025-3-26 06:34:51
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商店街
发表于 2025-3-26 10:38:52
A Time and Sentiment Unification Model for Personalized Recommendationng items. Intuitively, users buying items online are influenced not only by their preferences and public attentions, but also by the crowd sentiment (i.e., the word of mouth) to the items. Specifically, users are likely to refuse an item whose most reviews are negative from the crowd. Therefore, a g
微不足道
发表于 2025-3-26 14:02:54
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mettlesome
发表于 2025-3-26 20:25:33
Personalized POI Groups Recommendation in Location-Based Social Networksnsist of POIs. POI Groups have a significant impact on people’s lives and urban planning. Every person has her/his own personalized POI Groups (PPGs) based on preferences and friendship in location-based social networks (LBSNs). However, there are almost no researches on this aspect in recommendatio