A New Framework for Unsupervised Semantic Discovery

Schiffman, Barry

This paper presents a new framework for the unsupervised discovery of semantic information, using a divide-and-conquer approach to take advantage of contextual regularities and to avoid problems of polysemy and sublanguages. Multiple sets of documents are formed and analyzed to create multiple sets of frames. The overall procedure is wholly unsupervised and domain independent. The end result will be a collection of sets of semantic frames that will be useful in a wide range of applications, including question-answering, information extraction, summarization and text generation.



More About This Work

Academic Units
Computer Science
Department of Computer Science, Columbia University
Columbia University Computer Science Technical Reports, CUCS-039-07
Published Here
April 27, 2011