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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