Semantic Relatedness Using Salient Semantic Analysis

Authors

  • Samer Hassan University of North Texas
  • Rada Mihalcea University of North Texas

Abstract

This paper introduces a novel method for measuring semantic relatedness using semantic profiles constructed from salient encyclopedic features. The model is built on the notion that the meaning of a word can be characterized by the salient concepts found in its immediate context. In addition to being computationally efficient, the new model has superior performance and remarkable consistency when compared to both knowledge-based and corpus-based state-of-the-art semantic relatedness models.

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Published

2011-08-04

How to Cite

Hassan, S., & Mihalcea, R. (2011). Semantic Relatedness Using Salient Semantic Analysis. Proceedings of the AAAI Conference on Artificial Intelligence, 25(1), 884-889. Retrieved from https://ojs.aaai.org/index.php/AAAI/article/view/7971

Issue

Section

AAAI Technical Track: Natural Language Processing