The Web offers rich relational data with different semantics. In this paper, we address the problem of document recommendation in a digital library, where the documents in questio...
Ding Zhou, Shenghuo Zhu, Kai Yu, Xiaodan Song, Bel...
Characterizing the relationship that exists between a person's social group and his/her personal behavior has been a long standing goal of social network analysts. In this pa...
In this work we present topic diversification, a novel method designed to balance and diversify personalized recommendation lists in order to reflect the user's complete spec...
Cai-Nicolas Ziegler, Sean M. McNee, Joseph A. Kons...
Knowledge discovery on social network data can uncover latent social trends and produce valuable findings that benefit the welfare of the general public. A growing amount of resea...
In traditional text clustering methods, documents are represented as "bags of words" without considering the semantic information of each document. For instance, if two ...
Xiaohua Hu, Xiaodan Zhang, Caimei Lu, E. K. Park, ...