Abstract
Text information processing is one of the important topics in data mining. It involves the techniques of statistics, machine learning, pattern recognition etc. In the age of big data, a huge amount of text data has been accumulated. At present, the most effective text processing way is classifying them before mining. Therefore, it has attracted great interests of scholars and researchers, and many constructive results have been achieved. But along with the increasing of training samples, the shortages of techniques and limits of their application have appeared gradually. In this paper, we propose a new strategy for classifying documents based on Huffman tree. Firstly, we find out all the candidate classifications by generating a Huffman tree, and then we design a quality measure to select the final classification. Our experiment results show that the proposed algorithm is effective and feasible.
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Liu, Y., Wen, Y., Yuan, D., Cuan, Y. (2014). A Huffman Tree-Based Algorithm for Clustering Documents. In: Luo, X., Yu, J.X., Li, Z. (eds) Advanced Data Mining and Applications. ADMA 2014. Lecture Notes in Computer Science(), vol 8933. Springer, Cham. https://doi.org/10.1007/978-3-319-14717-8_49
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DOI: https://doi.org/10.1007/978-3-319-14717-8_49
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-14716-1
Online ISBN: 978-3-319-14717-8
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