Sequential Pattern Mining using FCA and Pattern Structures for Analyzing Visitor Trajectories in a Museum

Nyoman Juniarta 1 Miguel Couceiro 1 Amedeo Napoli 1 Chedy Raïssi 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 on mining visitor trajectories in Hecht Museum (Haifa, Israel), within the framework of CrossCult Eu-ropean 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 in the framework of FCA, namely the mining of subsequences without any constraint and the mining of frequent contiguous subsequences. Both approaches are based on 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.
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Nyoman Juniarta, Miguel Couceiro, Amedeo Napoli, Chedy Raïssi. Sequential Pattern Mining using FCA and Pattern Structures for Analyzing Visitor Trajectories in a Museum. CLA 2018 - The 14th International Conference on Concept Lattices and Their Applications, Jun 2018, Olomouc, Czech Republic. ⟨hal-01887914⟩

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