To improve the search results for socially-connect users, we propose a ranking framework, Social Network Document Rank (SNDocRank). This framework considers both document contents...
Liang Gou, Hung-Hsuan Chen, Jung-Hyun Kim, Xiaolon...
Building on previous work on how to model contextual information for desktop search and how to implement semantically rich information exchange in social networks, we define a new...
Abstract— The incomplete information about the Web structure causes inaccurate results of various ranking algorithms. In this paper, we propose a solution to this problem by form...
The problem of evaluating scientific publications and their authors is important, and as such has attracted increasing attention. Recent graph-theoretic ranking approaches have d...
Ding Zhou, Sergey A. Orshanskiy, Hongyuan Zha, C. ...
Given a network, we are interested in ranking sets of nodes that score highest on user-specified criteria. For instance in graphs from bibliographic data (e.g. PubMed), we would l...