Paper: Extracting Comparative Sentences from Korean Text Documents Using Comparative Lexical Patterns and Machine Learning Techniques

ACL ID P09-2039
Title Extracting Comparative Sentences from Korean Text Documents Using Comparative Lexical Patterns and Machine Learning Techniques
Venue Annual Meeting of the Association of Computational Linguistics
Session Short Paper
Year 2009
Authors

This paper proposes how to automatically identify Korean comparative sentences from text documents. This paper first investigates many comparative sentences referring to pre- vious studies and then defines a set of compar- ative keywords from them. A sentence which contains one or more elements of the keyword set is called a comparative-sentence candidate. Finally, we use machine learning techniques to eliminate non-comparative sentences from the candidates. As a result, we achieved signifi- cant performance, an F1-score of 88.54%, in our experiments using various web documents.