Abstract
We recently proposed a novel sentential association based approach SAT-MOD for text classification, which views a sentence rather than a document as an association transaction, and uses a novel heuristic called MODFIT to select the most significant itemsets for constructing a category classifier. Based on SAT-MOD, we have developed a prototype system called SAT-Class. In this demo, we demonstrate the effectiveness of our text classification system, and also the readability and refinability of acquired classification rules.
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Feng, J., Liu, H., Feng, Y. (2005). Sentential Association Based Text Classification Systems. In: Zhang, Y., Tanaka, K., Yu, J.X., Wang, S., Li, M. (eds) Web Technologies Research and Development - APWeb 2005. APWeb 2005. Lecture Notes in Computer Science, vol 3399. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-31849-1_101
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DOI: https://doi.org/10.1007/978-3-540-31849-1_101
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