UMBC ebiquity

UMBC_EBIQUITY-CORE: Semantic Textual Similarity Systems

Authors: Lushan Han, Abhay L. Kashyap, Tim Finin, James Mayfield, and Johnathan Weese

Book Title: Proceedings of the Second Joint Conference on Lexical and Computational Semantics

Date: June 13, 2013

Abstract: We describe three semantic text similarity systems developed for the *SEM 2013 STS shared task and the results of the corresponding three runs. All of them used a word similarity feature that combined LSA word similarity and WordNet knowledge. The first run, which achieved the top mean score on the task of all the submissions, used a simple term alignment algorithm. The other two runs, ranked second and fourth, used SVM models to combine a larger sets of features.

Type: InProceedings

Organization: Association for Computational Linguistics

Tags: natural language processing, language, semantics

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  1. (Publication) UMBC_EBIQUITY-CORE: Semantic Textual Similarity Systems has resource (Resource) UMBC webbase corpus