Phrase pair classification for identifying subtopics

Authors:
Sujatha Das;Prasenjit Mitra;C. Lee Giles
Affiliations:
Department of Computer Science and Engineering, The Pennsylvania State University, University Park, PA;School of Information Science and Technology, The Pennsylvania State University, University Park, PA;School of Information Science and Technology, The Pennsylvania State University, University Park, PA
Venue:
ECIR'12 Proceedings of the 34th European conference on Advances in Information Retrieval
Year:
2012

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Abstract

Automatic identification of subtopics for a given topic is desirable because it eliminates the need for manual construction of domain-specific topic hierarchies. In this paper, we design features based on corpus statistics to design a classifier for identifying the (subtopic, topic) links between phrase pairs. We combine these features along with the commonly-used syntactic patterns to classify phrase pairs from datasets in Computer Science and WordNet. In addition, we show a novel application of our is-a-subtopic-of classifier for query expansion in Expert Search and compare it with pseudo-relevance feedback.