Towards an automatic characterization of criteria

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Abstract

The number of documents is growing exponentially with the rapid expansion of the Web. The new challenge for Internet users is now to rapidly find appropriate data to their requests. Thus information retrieval, automatic classification and detection of opinions appear as major issues in our information society. Many efficient tools have already been proposed to Internet users to ease their search over the web and support them in their choices. Nowadays, users would like genuine decision tools that would efficiently support them when focusing on relevant information according to specific criteria in their area of interest. In this paper, we propose a new approach for automatic characterization of such criteria. We bring out that this approach is able to automatically build a relevant lexicon for each criterion. We then show how this lexicon can be useful for documents classification or segmentation tasks. Experiments have been carried out with real datasets and show the efficiency of our proposal. © 2011 Springer-Verlag Berlin Heidelberg.

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APA

Duthil, B., Trousset, F., Roche, M., Dray, G., Plantié, M., Montmain, J., & Poncelet, P. (2011). Towards an automatic characterization of criteria. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6860 LNCS, pp. 457–465). Springer Verlag. https://doi.org/10.1007/978-3-642-23088-2_34

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