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1
MAD : une plateforme mobile pour l'annotation de document vers la classification
In: CORIA-CIFED 2014 ; https://hal.archives-ouvertes.fr/hal-01247976 ; CORIA-CIFED 2014, Mar 2014, Nancy, France. pp.223-238 (2014)
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MAD : une plateforme mobile pour l'annotation de document vers la classification. ...
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3
How ontology based information retrieval systems may benefit from lexical text analysis
In: New Trends of Research in Ontologies and Lexical Resources ; https://hal.archives-ouvertes.fr/hal-00797143 ; Oltramari, Alessandro; Vossen, Piek; Qin, Lu; Hovy, Eduard. New Trends of Research in Ontologies and Lexical Resources, 15, Springer, pp.209-230, 2013, Theory and Applications of Natural Language Processing, 978-3-642-31781-1 (2013)
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4
Opinion Extraction Applied to Criteria
In: 23rd International Conference on Database and Expert Systems Applications ; DEXA: Database and Expert Systems Applications ; https://hal-lirmm.ccsd.cnrs.fr/lirmm-00732663 ; DEXA: Database and Expert Systems Applications, Sep 2012, Vienna, Austria. pp.457-465, ⟨10.1007/978-3-642-32597-7_44⟩ ; http://www.dexa.org/ (2012)
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5
Towards an Automatic Characterization of Criteria
In: 22nd International Conference on Database and Expert Systems Applications ; DEXA: Database and Expert Systems Applications ; https://hal-lirmm.ccsd.cnrs.fr/lirmm-00723579 ; DEXA: Database and Expert Systems Applications, Aug 2011, Toulouse, France. pp.457-465, ⟨10.1007/978-3-642-23088-2_34⟩ ; http://www.dexa.org/previous/dexa2011/index.html (2011)
Abstract: International audience ; 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.
Keyword: [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]; [INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR]; [INFO.INFO-TT]Computer Science [cs]/Document and Text Processing; [INFO.INFO-WB]Computer Science [cs]/Web; [SPI.OTHER]Engineering Sciences [physics]/Other; Classification; Criteria characterization; Mutual information; Segmentation
URL: https://doi.org/10.1007/978-3-642-23088-2_34
https://hal-lirmm.ccsd.cnrs.fr/lirmm-00723579/file/DEXA2011Criteria.pdf
https://hal-lirmm.ccsd.cnrs.fr/lirmm-00723579/document
https://hal-lirmm.ccsd.cnrs.fr/lirmm-00723579
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6
Towards an Automatic Characterization of Criteria
In: DEXA ; DEXA, 22nd International Conference on Database and Expert Systems Applications ; https://hal.archives-ouvertes.fr/hal-00804737 ; DEXA, 22nd International Conference on Database and Expert Systems Applications, Aug 2011, TOULOUSE, France. pp.1 (2011)
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