Výsledky vyhledávání - "Laurent Candillier"

Active learning in the real-world design and analysis of the Nomao challenge

Autor: Vincent Lemaire, Laurent Candillier

Publikováno v: IJCNN

Active Learning is an active area of research in the Machine Learning and Data Mining communities. In parallel, needs for efficient active learning methods are raised in real-world applications. As an illustration, we present in this paper an active

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::fe0c7ffef7a563244fb2963f81d4d13d
https://doi.org/10.1109/ijcnn.2013.6706908

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State-of-the-Art Recommender Systems

Autor: Kris Jack, Frank Meyer, Laurent Candillier, Françoise Fessant

The aim of Recommender Systems is to help users to find items that they should appreciate from huge catalogues. In that field, collaborative filtering approaches can be distinguished from content-based ones. The former is based on a set of user ratin

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::c2fac135f9109e941802ef162458df15
https://doi.org/10.4018/978-1-60566-306-7.ch001

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Designing Specific Weighted Similarity Measures to Improve Collaborative Filtering Systems

Autor: Frank Meyer, Laurent Candillier, Françoise Fessant

Publikováno v: Advances in Data Mining. Medical Applications, E-Commerce, Marketing, and Theoretical Aspects ISBN: 9783540707172
ICDM

The aim of collaborative filteringis to help usersto find itemsthat they should appreciate from huge catalogues. In that field, we can distinguish user-basedfrom item-basedapproaches. The former is based on the notion of user neighbourhoods while the

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::cfccc43d9f9c3ff86985fc191c1f8c56
https://doi.org/10.1007/978-3-540-70720-2_19

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Comparing State-of-the-Art Collaborative Filtering Systems

Autor: Marc Boullé, Frank Meyer, Laurent Candillier

Publikováno v: Machine Learning and Data Mining in Pattern Recognition ISBN: 9783540734987
MLDM

Collaborative filteringaims at helping usersfind itemsthey should appreciate from huge catalogues. In that field, we can distinguish user-based, item-basedand model-basedapproaches. For each of them, many options play a crucial role for their perform

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::275795386beb943ededb85d4a6a7789c
https://doi.org/10.1007/978-3-540-73499-4_41

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Mining XML Documents

Autor: Laurent Candillier, Alexandre Termier, Patrick Gallinari, Marie Christine Rousset, Anne-Marie Vercoustre, Ludovic Denoyer

Publikováno v: Data Mining Patterns: New Methods and Applications
P. Poncelet, F. Masseglia, M. Teisseire. Data Mining Patterns: New Methods and Applications, Information Science Reference, pp.198-219, 2007, ⟨10.4018/978-1-59904-162-9.ch009⟩

XML documents are becoming ubiquitous because of their rich and flexible format that can be used for a variety of applications. Giving the increasing size of XML collections as information sources, mining techniques that traditionally exist for text

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::393a03f98b3c580ca3117064d9e04964
https://inria.hal.science/inria-00188899/file/XML-MiningChapter_final.pdf

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Transforming XML Trees for Efficient Classification and Clustering

Autor: Laurent Candillier, Isabelle Tellier, Fabien Torre

Publikováno v: Lecture Notes in Computer Science ISBN: 3540349626
Lecture Notes in Computer Science ISBN: 9783540349624
INEX

Most of the existing methods we know to tackle datasets of XML documents directly work on the trees representing these XML documents. We investigate in this paper the use of a different kind of representation for the manipulation of XML documents. Ou

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6cd72ed8d927564f40e3d1c359cfc0c0
https://doi.org/10.1007/11766278_36

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Cascade Evaluation of Clustering Algorithms

Autor: Isabelle Tellier, Fabien Torre, Olivier Bousquet, Laurent Candillier

Publikováno v: Lecture Notes in Computer Science ISBN: 9783540453758
ECML

This paper is about the evaluation of the results of clustering algorithms, and the comparison of such algorithms. We propose a new method based on the enrichment of a set of independent labeled datasets by the results of clustering, and the use of a

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::7fa53d6a3c841051707e72a237bd54a3
https://doi.org/10.1007/11871842_54

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SSC: Statistical subspace clustering

Autor: Olivier Bousquet, Isabelle Tellier, Fabien Torre, Laurent Candillier

Publikováno v: Scopus-Elsevier
4th International Conference on Machine Learning and Data Mining in Pattern Recognition
4th International Conference on Machine Learning and Data Mining in Pattern Recognition, 2005, Leipzig, Georgia. pp.100--109
Machine Learning and Data Mining in Pattern Recognition ISBN: 9783540269236
MLDM

International audience; Subspace clustering is an extension of traditional clustering that seeks to find clusters in different subspaces within a dataset. This is a particularly important challenge with high dimensional data where the curse of dimens

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1e389694a0ebaec6cc38edac5379ee50
http://www.scopus.com/inward/record.url?eid=2-s2.0-26944472379&partnerID=MN8TOARS

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