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Title:
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A NOVEL SEMANTIC APPROACH TO DOCUMENT COLLECTIONS |
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Author(s):
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Andrea Addis , Manuela Angioni , Giuliano Armano , Roberto Demontis , Franco Tuveri , Eloisa Vargiu |
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ISBN:
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978-972-8924-60-7 |
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Editors:
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António Palma dos Reis |
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Year:
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2008 |
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Edition:
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Single |
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Keywords:
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Text Categorization, Document Collections, Intelligent Software Systems, Machine Learning |
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Type:
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Full Paper |
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First Page:
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53 |
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Last Page:
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60 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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Available document collections are more and more required for supervised text categorization tasks. They typically are
collections of documents classified by domain engineers. In this paper, we propose a semantic text categorization
approach able to automatically create document collections in which documents are classified according to WordNet
Domains taxonomy. Experiments have been performed by training a classifier with an automatic document collection and
comparing results with those obtained by training the same classifier on a hand-made document collection. Experimental
results point out that, on average, the performances of the automatic approach are quite similar to those obtained on a
document collection classified by domain engineers. |
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