[Paper] A comparative Study of Two Short Text Semantic Similarity Measures

    Book Series -
    Book Title  - Agent and Multi-Agent Systems: Technologies and Applications
    Chapter Title  - A Comparative Study of Two Short Text Semantic Similarity Measures
    First Page  - 172
    Last Page  - 181
    Copyright  - 2008
    Author  - James O’Shea
    Author  - Zuhair Bandar
    Author  - Keeley Crockett
    Author  - David McLean
    DOI  - 10.1007/978-3-540-78582-8_18
    Link  - http://www.springerlink.com/content/v0867641u342pm2

James O’Shea¹ , Zuhair Bandar¹ , Keeley Crockett¹  and David McLean¹ 

(1)	Department of Computing and Mathematics, Manchester Metropolitan University, Chester St., Manchester, M1 5GD, United Kingdom

Abstract

This paper describes a comparative study of STASIS and LSA. These measures of semantic similarity can be applied to short texts for use in Conversational Agents (CAs). CAs are computer programs that interact with humans through natural language dialogue. Business organizations have spent large sums of money in recent years developing them for online customer self-service, but achievements have been limited to simple FAQ systems. We believe this is due to the labour-intensive process of scripting, which could be reduced radically by the use of short-text semantic similarity measures. “Short texts” are typically 10-20 words long but are not required to be grammatically correct sentences, for example spoken utterances and text messages. We also present a benchmark data set of 65 sentence pairs with human-derived similarity ratings. This data set is the first of its kind, specifically developed to evaluate such measures and we believe it will be valuable to future researchers.

Keywords  Natural Language - Semantic Similarity - Dialogue Management - User Modeling - Benchmark - Sentence

Important Points

• Discussion and summary of different kinds of similarities (Taxonomic, related, goal derived and radial)
  
• Introduction of a (small) test corpora and how the corpora was created. This includes some discussion on how humans rate.
• Statement that co-occurrence measures yield also high similarity values for antonyms