Document (#26597)

Author
Ruiz, M.E.
Srinivasan, P.
Title
Combining machine learning and hierarchical indexing structures for text categorization
Source
Advances in classification research, vol.10: proceedings of the 10th ASIS SIG/CR Classification Research Workshop. Ed.: Albrechtsen, H. u. J.E. Mai
Imprint
Medford, NJ : Information Today
Year
2001
Pages
S.107-124
Series
ASIS monograph series
Abstract
This paper presents a method that exploits the hierarchical structure of an indexing vocabulary to guide the development and training of machine learning methods for automatic text categorization. We present the design of a hierarchical classifier based an the divide-and-conquer principle. The method is evaluated using backpropagation neural networks, such as the machine learning algorithm, that leam to assign MeSH categories to a subset of MEDLINE records. Comparisons with traditional Rocchio's algorithm adapted for text categorization, as well as flat neural network classifiers, are provided. The results indicate that the use of hierarchical structures improves Performance significantly.
Theme
Automatisches Klassifizieren
Computerlinguistik

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