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...
In search engines, ranking algorithms measure the importance and relevance of documents mainly based on the contents and relationships between documents. User attributes are usual...
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. ...
Multimedia ranking algorithms are usually user-neutral and measure the importance and relevance of documents by only using the visual contents and meta-data. However, users’ int...
Liang Gou, Hung-Hsuan Chen, Jung-Hyun Kim, Xiaolon...
This paper introduces the problem of matching people names to their corresponding social network identities such as their Twitter accounts. Existing tools for this purpose build u...
Gae-won You, Seung-won Hwang, Zaiqing Nie, Ji-Rong...