In this paper, we study a novel problem Collective Active Learning, in which we aim to select a batch set of "informative" instances from a networking data set to query ...
The Internet and corporate intranets provide far more information than anybody can absorb. People use search engines to find the information they require. However, these systems t...
In this paper we use a Unified Relationship Matrix (URM) to represent a set of heterogeneous data objects (e.g., web pages, queries) and their interrelationships (e.g., hyperlinks...
Wensi Xi, Edward A. Fox, Weiguo Fan, Benyu Zhang, ...
In this paper, we propose a novel top-k learning to rank framework, which involves labeling strategy, ranking model and evaluation measure. The motivation comes from the difficul...
In the context of biomedical information retrieval (IR), this paper explores the relationship between the document’s global context and the query’s local context in an attempt ...