Publisher
Springer Berlin Heidelberg
Reference28 articles.
1. Agrawal, R., Srikant, R.: Fast algorithms for mining association rules in large databases. In: Proceedings of 20th International Conference on Very Large Data Bases (VLDB 1994), pp. 487–499 (1994)
2. Beil, F., Ester, M., Xu, X.: Frequent term-based text clustering. In: Proceedings of the Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 436–442 (2002)
3. Dasgupta, S., Ng, V.: Mine the easy, classify the hard: A semi-supervised approach to automatic sentiment classification. In: Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP, pp. 701–709 (2009)
4. Dasgupta, S., Ng, V.: Topic-wise, sentiment-wise, or otherwise? Identifying the hidden dimension for unsupervised text classification. In: Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing, pp. 580–589 (2009b)
5. Dey, L., Haque, S.K.M.: Opinion mining from noisy text data. In: Proceedings of the Second Workshop on Analytics for Noisy Unstructured Text Data (AND 2008), pp. 83–90. ACM, New York (2008)
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