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Titlebook: Web-Age Information Management; 16th International C Xin Luna Dong,Xiaohui Yu,Yizhou Sun Conference proceedings 2015 Springer International

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樓主: Malnutrition
71#
發(fā)表于 2025-4-2 22:38:25 | 只看該作者
Resorting Relevance Evidences to Cumulative Citation Recommendation for Knowledge Base Accelerationto address this problem, whose objective is to filter relevant documents from a chronological stream corpus and then recommend them as candidate citations with certain relevance estimation to target entities in KBs. The challenge of CCR is how to accurately category the candidate documents into diff
72#
發(fā)表于 2025-4-3 01:16:51 | 只看該作者
Relevance Search on Signed Heterogeneous Information Network Based on Meta-path Factorizationt types. Due to the semantics implied by network links, conventional research on relevance search is often based on meta-path in heterogeneous information networks. However, existing approaches mainly focus on studying non-signed information networks, without considering the polarity of the links in
73#
發(fā)表于 2025-4-3 04:32:29 | 只看該作者
Improving the Effectiveness of Keyword Search in Databases Using Query Logsd data (relational databases in particular), most existing work has focused on improving search result quality through designing better scoring functions, without giving explicit consideration to query logs. Our work presented in this paper taps into the wealth of information contained in query logs
74#
發(fā)表于 2025-4-3 09:30:01 | 只看該作者
cluTM: Content and Link Integrated Topic Model on Heterogeneous Information Networksl topic models assume the documents are independent and there are no correlations among them. However, in many real scenarios, a document may be interconnected with other documents and objects, and thus form a text related heterogeneous network, such as the DBLP bibliographic network. It is challeng
75#
發(fā)表于 2025-4-3 14:30:52 | 只看該作者
An Influence Field Perspective on Predicting User’s Retweeting Behaviornt profile for personalized recommendation and many other tasks. Retweeting prediction is of great significance. In this paper, we believe that user’s retweeting behavior is synthetically caused by the influence from other users and the post. By analogy with the concept of electric field in physics,
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