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Sequential Pattern Mining within Formal Concept Analysis for Analyzing Visitor Trajectories

Nyoman Juniarta 1 Miguel Couceiro 1 Amedeo Napoli 1
1 ORPAILLEUR - Knowledge representation, reasonning
Inria Nancy - Grand Est, LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery
Abstract : This paper presents our work about mining visitor trajectories, within the framework of CrossCult European Project about cultural heritage. We present a theoretical and practical research work about the characterization of visitor trajectories and the mining of these trajectories as sequences. The mining process is based on two approaches, namely the mining of subsequences without any constraint and the mining of frequent contiguous subsequences. Both approaches are defined within Formal Concept Analysis and its extension pattern structures. In parallel, a similarity measure allows us to build a hierarchical classification which is used for interpretation and characterization of the trajectories w.r.t. four well-known visiting styles in museum studies.
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https://hal.inria.fr/hal-02166655
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Submitted on : Thursday, June 27, 2019 - 9:00:37 AM
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Nyoman Juniarta, Miguel Couceiro, Amedeo Napoli. Sequential Pattern Mining within Formal Concept Analysis for Analyzing Visitor Trajectories. BDA 2018 - 34ème Conférence sur la Gestion de Données – Principes, Technologies et Applications, Oct 2018, Bucarest, Romania. ⟨hal-02166655⟩

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