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Poster communications

Application of sequential pattern mining to the analysis of visitor trajectories

Nyoman Juniarta 1 Amedeo Napoli 1
1 ORPAILLEUR - Knowledge representation, reasonning
Inria Nancy - Grand Est, LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery
Abstract : In this work, we demonstrate the proof of concept of clustering 254 visitors based on their trajectories in a museum. We used a real dataset from Haifa Museum, where each trajectory is treated as a sequence of itemsets. We applied simACS as a similarity measure between any two sequences.
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Poster communications
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https://hal.inria.fr/hal-01667442
Contributor : Nyoman Juniarta <>
Submitted on : Tuesday, December 19, 2017 - 1:33:24 PM
Last modification on : Friday, January 29, 2021 - 10:26:02 AM

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Nyoman Juniarta, Amedeo Napoli. Application of sequential pattern mining to the analysis of visitor trajectories. BDA 2017 - 33ème conférence sur la Gestion de Données — Principes, Technologies et Applications, Nov 2017, Nancy, France. ⟨hal-01667442⟩

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