Paper: Align, Disambiguate and Walk: A Unified Approach for Measuring Semantic Similarity

ACL ID P13-1132
Title Align, Disambiguate and Walk: A Unified Approach for Measuring Semantic Similarity
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2013
Authors

Semantic similarity is an essential com- ponent of many Natural Language Pro- cessing applications. However, prior meth- ods for computing semantic similarity of- ten operate at different levels, e.g., sin- gle words or entire documents, which re- quires adapting the method for each data type. We present a unified approach to se- mantic similarity that operates at multiple levels, all the way from comparing word senses to comparing text documents. Our method leverages a common probabilistic representation over word senses in order to compare different types of linguistic data. This unified representation shows state-of- the-art performance on three tasks: seman- tic textual similarity, word similarity, and word sense coarsening.