This paper develops a general, formal framework for modeling term dependencies via Markov random fields. The model allows for arbitrary text features to be incorporated as eviden...
Most research in the field of anaphora or coreference detection has been limited to noun phrase coreference, usually on a restricted set of entities, such as ACE entities. In par...
Sameer S. Pradhan, Lance A. Ramshaw, Ralph M. Weis...
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, ...
Recently, models based on conditional random fields (CRF) have produced promising results on labeling sequential data in several scientific fields. However, in the vision task of c...
Huazhong Ning, Wei Xu, Yihong Gong, Thomas S. Huan...
In this paper, we propose a semi-supervised learning approach for classifying program (bot) generated web search traffic from that of genuine human users. The work is motivated by...
Hongwen Kang, Kuansan Wang, David Soukal, Fritz Be...