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Communication Dans Un Congrès Année : 2019

Weaving Information Propagation: Modeling The Way Information Spreads In Document Collections

Résumé

Information usually spreads between people by the mean of textual documents. During such propagation, a piece of information can either remain the same or mutate. We propose to formulate information spread with a set of time-ordered document chains along which some information has likely been transmitted. This formulation is different from the usual graph view of a transmission process as it integrates a notion of lineage of the information. We also propose a way to construct a candidate set of document chains for the information propagation in a corpus of documents. We show that most of the chains have been judged as plausible by human experts.
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Dates et versions

hal-02299994 , version 1 (29-09-2019)

Identifiants

Citer

Charles Huyghues-Despointes, Leila Khouas, Julien Velcin, Sabine Loudcher. Weaving Information Propagation: Modeling The Way Information Spreads In Document Collections. 32nd Canadian Conference on Artificial Intelligence (Canadian AI), May 2019, Kingston, Canada. ⟨10.1007/978-3-030-18305-9_35⟩. ⟨hal-02299994⟩
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