Abstract
Hierarchical text classification concerning the relationship among categories has become an interesting problem recently. Most research has focused on tree-structured categories, but in reality directed acyclic graph (DAG) – structured categories, where a child category may have more than one parent category, appear more often. In this paper, we introduce three approaches, namely, flat, tree-based, and DAG-based, for solving the multi-label text classification problem in which categories are organized as a DAG, and documents are classified into both leaf and internal categories. We also present experimental results of the methods using SVMs as classifiers on the Reuters-21578 collection and our data set of research papers in Artificial Intelligence.
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Nguyen, C.D., Dung, T.A., Cao, T.H. (2005). Text Classification for DAG-Structured Categories. In: Ho, T.B., Cheung, D., Liu, H. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2005. Lecture Notes in Computer Science(), vol 3518. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11430919_36
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DOI: https://doi.org/10.1007/11430919_36
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26076-9
Online ISBN: 978-3-540-31935-1
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