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Communication Dans Un Congrès Année : 2015

Combining Advanced Information Retrieval and Text-Mining for Digital Humanities

Résumé

Digital Humanities make more and more structured and richly annotated corpora available. Most of this data rely on well known and established standards, such as TEI, which especially enable scientists to edit and publish their work. However, one of the remaining problems is to give adequate access to this rich data, in order to produce higher-order knowledge.

In this paper, we present an integrated environment combining an advanced search engine and text-mining techniques for hermeneutics in Digital Humanities. Relying on semantic web technologies, the search engine uses full text as well as complex embedding structures and offers a single interface to access rich and heterogeneous data and meta-data. Text-mining possibilities enable scholars to exhibit regularities in corpora. Results obtained on the Cartesian corpus illustrate these principles and tools.
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Dates et versions

hal-01712341 , version 1 (19-02-2018)

Identifiants

Citer

Antoine Widlöcher, Nicolas Béchet, Jean-Marc Lecarpentier, Yann Mathet, Julia Roger. Combining Advanced Information Retrieval and Text-Mining for Digital Humanities. DocEng '15: ACM Symposium on Document Engineering 2015, Sep 2015, Lausanne, Switzerland. pp.157-166, ⟨10.1145/2682571.2797067⟩. ⟨hal-01712341⟩
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