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Classification active de flux de documents avec identification des nouvelles classes

Mohamed-Rafik Bouguelia 1 yolande Belaïd 1 Abdel Belaïd 1 
1 READ - Recognition of writing and analysis of documents
LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery
Abstract : In this paper, we propose a stream-based semi-supervised active learning method for document classification, which is able to query (from an operator) the class labels of documents that are informative, according to an uncertainty measure. The method maintains a dynamically evolving graph topology of labelled document-representatives, which constitutes a covered feature space. The method is able to automatically discover the emergence of novel classes in the stream. An incoming document is identified as a member of a novel class or an existing class, depending on whether it is outside or inside the area covered by the known classes. Experiments on different real datasets show that the proposed method requires a small amount of the incoming documents to be labelled, in order to learn a model which achieves better or equal accuracy than to the usual supervised methods with fully labelled training documents.
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Submitted on : Friday, April 18, 2014 - 3:54:20 PM
Last modification on : Saturday, October 16, 2021 - 11:26:09 AM
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  • HAL Id : hal-00980698, version 1



Mohamed-Rafik Bouguelia, yolande Belaïd, Abdel Belaïd. Classification active de flux de documents avec identification des nouvelles classes. CIFED - Colloque International Francophone sur l'Écrit et le Document, Mar 2014, Nancy, France. pp.75-89. ⟨hal-00980698⟩



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