A cross-collection mixture model for comparative text mining
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
CWS: a comparative web search system
Proceedings of the 15th international conference on World Wide Web
Identifying comparative sentences in text documents
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Answering relationship queries on the web
Proceedings of the 16th international conference on World Wide Web
Extracting Product Comparisons from Discussion Boards
ICDM '07 Proceedings of the 2007 Seventh IEEE International Conference on Data Mining
Mining comparative sentences and relations
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
Comparative news summarization using linear programming
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: short papers - Volume 2
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Identifying comparative sentences in natural language is an important step for extracting comparative relations. To our knowledge, there is no research on identifying Chinese comparative sentences automatically. This paper first defines the problem of Chinese comparative sentence identification, and then proposes to use several classifiers to classify a Chinese sentence into either "comparative" or not. Various linguistic and statistical features have been explored, such as keywords and sequential patterns. Experimental results demonstrate the good effectiveness of the sequential patterns, i.e. the classifiers with sequential patterns can significantly outperform the traditional term-based classifier. We also empirically investigate the important factors that affect classification performance.