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

This paper proposes how to automatically identify Korean comparative sentences from text documents. This paper first investigates many comparative sentences referring to previous studies and then defines a set of comparative 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 significant performance, an F1-score of 88.54%, in our experiments using various web documents.