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Contextual Exploration (EC3): a strategy for the detection, extraction and visualization of target data

Abstract : EC3 is intended to extract relevant information from large heterogeneous and multilingual text data, in particular in WEB 3.0. The project is based on an original method: contextual exploration. EC3 does not need syntactic analysis, statistical analysis or a "general" ontology. EC3 uses only small ontologies called "linguistic ontologies" that express the linguistic knowledge of a user who must concentrate on the relevant information from one point of view. This is why EC3 works very quickly on large corpus, whose components can be both whole books as well as "short texts": SMS to books. At the output, EC3 offers a visual representation of information using an original approach: the "Memory Islands". EC3 is implanted in the ACASA / LIP6 team. EC3 is tested on the large digitized corpus provided by the Labex OBVIL «Observatoire de la Vie Littéraire», in partnership with the Bibliothèque Nationale de France (http://obvil.paris-sorbonne.fr/). OBVIL intends to develop all the resources offered by digitization and computer applications to examine French literature from the sixteenth to the twentieth century, English and American literature, Italian literature, Spanish literature, in its most traditional formats and media Or the most innovative.
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https://hal-cnam.archives-ouvertes.fr/hal-02555454
Contributor : Hammou Fadili <>
Submitted on : Monday, April 27, 2020 - 12:08:52 PM
Last modification on : Thursday, October 15, 2020 - 12:18:03 PM

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Hammou Fadili, Christophe Jouis, Jean-Gabriel Ganascia, Iana Atanassova, Bin Yang, et al.. Contextual Exploration (EC3): a strategy for the detection, extraction and visualization of target data. 4th International Conference on Big Data Analysis and Data Mining, Sep 2017, Paris, France. pp.67, ⟨10.4172/2324-9307-C1-014⟩. ⟨hal-02555454⟩

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