Kernelized sorting is an approach for matching objects from two sources (or domains) that does not require any prior notion of similarity between objects across the two sources. U...
Jagadeesh Jagarlamudi, Seth Juarez, Hal Daum&eacut...
Web text has been successfully used as training data for many NLP applications. While most previous work accesses web text through search engine hit counts, we created a Web Corpu...
This paper introduces dual decomposition as a framework for deriving inference algorithms for NLP problems. The approach relies on standard dynamic-programming algorithms as oracl...
Alexander M. Rush, David Sontag, Michael Collins, ...
Many tasks in computational linguistics can be regarded as configuration problems. In this paper, we introduce the notion of lexicalised multi-dimensional configuration problems (l...
We developed a fully automated Information Retrieval System which uses advanced natural language processing techniques to enhance the effectiveness of traditional key-word based d...