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Thomas Guyet
28
Documents
Identifiants chercheurs
- thomas-guyet
- 0000-0002-4909-5843
- Google Scholar : https://scholar.google.com/citations?user=cuNKrFoAAAAJ
- IdRef : 171949307
Présentation
Research interests
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My research area is artificial intelligence (AI) with a multidisciplinary approach - algorithmic, design methodologies and cognitive science. I am particularly interested in discovering spatial and temporal patterns in semantically rich datasets. My areas of application are related to agronomy (mainly landscapes) and health (care pathways analysis).
My first research direction is the **temporal and spatial pattern mining**. Data from the observation of living systems (agricultural and medical systems) have a strong spatial or temporal dimension. But the spatial and temporal information is often underutilized in the data mining algorithms. The challenge lies in identifying new kind of temporal/spatial patterns that have valuable properties to make possible their extraction by complete and correct algorithms. A recent approach I'm developping is the use declarative programming, more especially **[Answer Set Programming (ASP)](https://www.cs.utexas.edu/users/vl/papers/wiasp.pdf)** with [clingo](https://potassco.org), to mix pattern mining and reasonning.
My second research direction aims at better including the user in the loop of knowledge discovery. Specifically, I am interested in implementing **interactive systems to support users in their exploration process** of large datasets. To acheive this goal I propose an enactive point of view of the data interpretation that brings creative solutions to take into account the cognitive ergonomy of the knowledge discovery tools.
Publications
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NegPSpan: efficient extraction of negative sequential patterns with embedding constraintsData Mining and Knowledge Discovery, 2020, 34, pp.563-609. ⟨10.1007/s10618-019-00672-w⟩
Article dans une revue
hal-03025572v1
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Programmation par ensembles réponses pour simuler l’assolement d’un paysageRevue des Sciences et Technologies de l'Information - Série RIA : Revue d'Intelligence Artificielle, 2015, Numéro spécial RFIA 2014, 29 (3-4), pp.28. ⟨10.3166/ria.29.293-320⟩
Article dans une revue
hal-01184092v1
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Autonomic Intrusion Detection: Adaptively Detecting Anomalies over Unlabeled Audit Data Streams in Computer NetworksKnowledge-Based Systems, 2014, 70, pp.103-117. ⟨10.1016/j.knosys.2014.06.018⟩
Article dans une revue
hal-01052810v1
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Clustering Flood Events from Water Quality Time-Series using Latent Dirichlet Allocation ModelWater Resources Research, 2013, 49 (12), pp.8187-8199. ⟨10.1002/2013WR014086⟩
Article dans une revue
halshs-00906292v1
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Fouille de motifs temporels négatifsEGC 2018 - 18ème Conférence Internationale sur l'Extraction et la Gestion des Connaissances, Jan 2018, Paris, France. pp.263-268
Communication dans un congrès
hal-01657540v1
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Purchase Signatures of Retail CustomersPAKDD 2017 - The Pacific-Asia Conference on Knowledge Discovery and Data Mining, May 2017, Jeju, South Korea
Communication dans un congrès
hal-01639795v1
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Mining relevant interval rulesInternational Conference on Formal Concept Analysis, Jun 2017, Rennes, France
Communication dans un congrès
hal-01584981v1
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Fouille de motifs séquentiels avec ASPExtraction et Gestion de Connaissances (EGC), 2016, Reims, France
Communication dans un congrès
hal-01239501v1
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Packing graphs with ASP for landscape simulationIJCAI 2016 - 25th International joint conference on artificial intelligence , Jul 2016, New-york, United States. pp.8
Communication dans un congrès
hal-01327368v1
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Knowledge-based Sequence Mining with ASPIJCAI 2016- 25th International joint conference on artificial intelligence, Jul 2016, New-york, United States. pp.8
Communication dans un congrès
hal-01327363v1
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Sequential pattern mining for customer relationship management analysisAtelier GAST@EGC2015, Jan 2015, Luxembourg, Luxembourg
Communication dans un congrès
hal-01097466v1
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Evaluating Distance Measures and Times Series Clustering for Temporal Patterns RetrievalIEEE IRI - 15th IEEE International Conference on Information Retrieval and Reuse, Aug 2014, San Francisco, United States
Communication dans un congrès
hal-01052805v1
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Using Answer Set Programming for pattern miningIntelligence Artificielle Fondamentale, Jun 2014, Angers, France
Communication dans un congrès
hal-01069092v1
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1d-SAX : une nouvelle représentation symbolique pour les séries temporellesConférence Extraction et Gestion de Connaissances, Jan 2014, Rennes, France
Communication dans un congrès
hal-00916970v1
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1d-SAX: A Novel Symbolic Representation for Time SeriesInternational Symposium on Intelligent Data Analysis, 2013, United Kingdom. pp.273-284, ⟨10.1007/978-3-642-41398-8_24⟩
Communication dans un congrès
halshs-00912512v1
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Extraction incrémentale de séquences fréquentes dans un flux d'itemsetsExtraction et Gestion de Connaissances (EGC'2012), Jan 2012, Bordeaux, France
Communication dans un congrès
hal-00648893v1
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Incremental mining of frequent sequences from a window sliding over a stream of itemsetsJournées Intelligence Artificielle Fondamentale, May 2012, France. pp.153-162
Communication dans un congrès
hal-00757120v1
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Extraction de motifs temporels à partir de séquences d'événements avec intervalles temporelsExtraction et Gestion de Connaissances, Jan 2011, Brest, France
Communication dans un congrès
inria-00547629v1
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Extracting temporal patterns from interval-based sequencesInternational Join Conference on Artificial Intelligence (IJCAI), Jul 2011, Barcelone, Spain
Communication dans un congrès
inria-00618444v1
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Online and Adaptive anomaly Detection: detecting intrusions in unlabelled audit data streamsEGC 2009, 2009, Strasbourg, France
Communication dans un congrès
inria-00460723v1
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Diagnostic multi-sources adaptatif Application à la détection d'intrusion dans des serveurs WebEGC 2009, 2009, Strasbourg, France
Communication dans un congrès
inria-00460721v1
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A General Framework for Adaptive and Online Detection of Web attacks18th International World Wide Web Conference - WWW 2009, Apr 2009, Madrid, Spain
Communication dans un congrès
inria-00461391v1
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Mining temporal patterns with quantitative intervals4th International Workshop on Mining Complex Data, (IEEE ICDM) Workshop, 2008, Italy. pp.10
Communication dans un congrès
hal-00431445v1
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Understanding Customer Attrition at an Individual Level: a New Model in Grocery Retail ContextInternational Conference on Extending Database Technology (EDBT), Mar 2016, Bordeaux, France. ⟨10.5441/002/edbt.2016.87⟩
Poster de conférence
hal-01405172v1
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Efficiency Analysis of ASP Encodings for Sequential Pattern Mining TasksBruno Pinaud; Fabrice Guillet; Bruno Cremilleux; Cyril de Runz. Advances in Knowledge Discovery and Management, 7, Springer, pp.41--81, 2017, 978-3-319-65405-8
Chapitre d'ouvrage
hal-01631879v1
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LogAnalyzer : monitoring adaptatif d'un flux de données2010
Autre publication scientifique
inria-00460682v1
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NegPSpan: efficient extraction of negative sequential patterns with embedding constraints2018
Pré-publication, Document de travail
hal-01743975v2
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Self-adaptive web intrusion detection system[Research Report] RR-6989, INRIA. 2009, pp.24
Rapport
inria-00406450v1
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