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...
Simple word matching between the user query and document is common, as are mis-matches of meaning that occur as a consequence, and errors in recall. These defects in the "bag...
In this paper we study the problem of finding most topical named entities among all entities in a document, which we refer to as focused named entity recognition. We show that th...
We present an algorithm for video retrieval that fuses the decisions of multiple retrieval agents in both text and image modalities. While the normalization and combination of evi...
We present an extension of a computational cognitive model of social tagging and exploratory search called the semantic imitation model. The model assumes a probabilistic represen...
Wai-Tat Fu, Thomas George Kannampallil, Ruogu Kang