ESPY
发表于 2025-3-28 15:20:05
Detecting Anti-majority Opinionists Using Value-Weighted Mixture Voter Model,ct that some people have a tendency to disagree with any opinion expressed by the majority. We extend the value-weighted voter model to include this phenomenon with the anti-majoritarian tendency of each node as a new parameter, and learn this parameter as well as the value of each opinion from a se
apiary
发表于 2025-3-28 21:13:58
Using Ontologies in Semantic Data Mining with SEGS and g-SEGS,to the data, the amount of semantic data is rapidly growing. The data mining community is faced with a paradigm shift: instead of mining the abundance of empirical data supported by the background knowledge, the new challenge is to mine the abundance of knowledge encoded in domain ontologies, constr
白杨
发表于 2025-3-29 01:20:12
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Adulterate
发表于 2025-3-29 04:49:04
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寻找
发表于 2025-3-29 07:31:05
Network Effects on Tweeting,nformation exchange than Twitter.com. In this paper, we study large-scale graph properties and lesser-studied local graph structures of the explicit social network and the implicit retweet network in order to better understand the relationship between socialization and tweeting behaviors. In particu
证实
发表于 2025-3-29 14:15:40
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挑剔为人
发表于 2025-3-29 18:04:41
Frontiers in African Business Researchpt to remove unwanted rank equalities. Through experiments we show that . produces ranking functions having predictive performance comparable to that of a state-of-the-art instance ranking algorithm. This makes . a valuable alternative when monotonicity is desired or mandatory.
分期付款
发表于 2025-3-29 23:09:58
C. Santano,M. Pérez de Lara,J. Pintormber of communities and topics automatically, Hierarchical/Dirichlet Process Mixture model (H/DPM) is employed. Gibbs sampling based approach is adopted to learn the model parameters. Experiments are conducted on the co-author network extracted from DBLP where each author is associated with his/her
Androgen
发表于 2025-3-30 02:38:25
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Affectation
发表于 2025-3-30 06:19:56
Die Siebenbürger Sachsen und Österreiche this problem we incorporate external contextual information (e.g. time of the day) into route recognition from trajectory. We develop a technique to determine from the historical data how the probability of a route depends on contextual features and adjust (post-correct) the route recognition outp