Abstract
This chapter is concerned with the schemes of evaluating text clustering systems or approaches.
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References
Brun, M., Sima, C., Hua, J., Lowey, J., Carroll, B., Suha, E., Doughertya, E.R.: Model-based evaluation of clustering validation measures. Pattern Recogn. 40, 807–824 (2007)
Halkidi, M., Batistakis, Y., Vazirgiannis, M.: On clustering validation techniques. J. Intell. Inf. Syst. 17, 107–145 (2001)
Jo, T.: The Implementation of Dynamic Document Organization Using the Integration of Text Clustering and Text Categorization, University of Ottawa (2006)
Jo, T.: Inverted Index based modified version of KNN for text categorization. J. Inf. Process. Syst. 4, 17–26 (2008)
Jo, T.: Neural text categorizer for exclusive text categorization. J. Inf. Process. Syst. 4, 77–86 (2008)
Jo, T., Lee, M.: The evaluation measure of text clustering for the variable number of clusters. Lect. Notes Comput. Sci. 4492, 871–879 (2007)
Sebastiani, F.: Machine learning in automated text categorization. ACM Comput. Surv. 34, 1–47 (2002)
Vendramin, L., Campello, R., Hruschka E.R.: On the comparison of relative clustering validity criteria. In: Proceedings of the 2009 SIAM International Conference on Data Mining, pp. 733–744 (2009)
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Jo, T. (2019). Text Clustering: Evaluation. In: Text Mining. Studies in Big Data, vol 45. Springer, Cham. https://doi.org/10.1007/978-3-319-91815-0_12
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DOI: https://doi.org/10.1007/978-3-319-91815-0_12
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