TDSS: A New Word Sense Representation Framework for Information Retrieval

Word sense representation is important in the tasks of information retrieval (IR). Existing lexical databases, e.g., WordNet, and automated word sense representing approaches often use only one view to represent a word, and may not work well in the tasks which are sensitive to the contexts, e.g., query rewriting. In this paper, we propose a new framework to represent a word sense simultaneously in two views, explanation view and context view. We further propose an novel method to automatically learn such representations from large scale of query logs. Experimental results show that our new sense representations can better handle word substitutions in a query rewriting task.