Phrase pair classification for identifying subtopics

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. © 2012 Springer-Verlag Berlin Heidelberg.