The existence of the centrality metric is formally proven, and the convergence of the Co-Rank is also shown so that it can be effectively applied for the ranking. The results of experiments on synthetic and real-world networks show the effectiveness of our proposed algorithm. (C) 2019 ...
MultiRank: Co-ranking for objects and relations in multi-relational data The main aim of this paper is to design a co-ranking scheme for objects and relations in multi-relational data. It has many important applications in data ... Ng, Michael K.,X Li,Y Ye - DBLP 被引量: 120发表: ...
The former three steps are iterated until the ranking performance of base ranker begins to decrease on validation set. In this method, we assume that the unlabeled data follows the same generative distribution as the labeled data. The effectiveness of the presented co-ranking algorithm is ...
In this paper, we present an adaptive graph-based personalized recommendation method based on co-ranking and query-based collaborative diffusion. By utilizing the unique network structure of n-partite heterogeneous graph, we attempt to address the problem of personalized recommendation in a two-layer ...
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Paper阅读之:Co-HITS-Ranking Based Query-Focused Multi-document Summarization,程序员大本营,技术文章内容聚合第一站。
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This co--ranking approach has been validated using data collected from DBLP and CiteSeer, and the results suggest that it is effective and efficient in ranking authors and publications based on limited numbers of citations in heterogeneous networks and that it has fast convergence. 展开 ...
Next, a co-ranking algorithm is proposed to estimate the confidence of each candidate, and the candidates with higher confidence will be extracted as opinion targets/words. In this way, different relations make cooperative effects on candidates' confidence estimation. Moreover, word preference is ...
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