Download e-book for iPad: Advances in Knowledge Discovery and Management: Volume 5 by Fabrice Guillet, Bruno Pinaud, Gilles Venturini, Djamel

Nonfiction 13

By Fabrice Guillet, Bruno Pinaud, Gilles Venturini, Djamel Abdelkader Zighed

ISBN-10: 3319237500

ISBN-13: 9783319237503

ISBN-10: 3319237519

ISBN-13: 9783319237510

This booklet is a set of consultant and novel works performed in facts Mining, wisdom Discovery, Clustering and type that have been initially provided in French on the EGC'2013 (Toulouse, France, January 2013) and EGC'2014 meetings (Rennes, France, January 2014). those meetings have been respectively the thirteenth and 14th versions of this occasion, which happens every year and that's now winning and recognized within the French-speaking neighborhood. This neighborhood used to be based in 2003 via the root of the French-speaking EGC society (EGC in French stands for "Extraction et Gestion des Connaissances" and ability "Knowledge Discovery and Management", or KDM).

This publication is aiming in any respect researchers attracted to those fields, together with PhD or MSc scholars, and researchers from public or inner most laboratories. It issues either theoretical and useful facets of KDM. The ebook is established in components referred to as "Applications of KDM to actual datasets" and "Foundations of KDM".

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1 Introduction Monitoring traffic on road networks is generally handled using dedicated sensors that provide estimations of the number of vehicles traversing the road portion on which they are deployed. e. highways and main arteries). K. fr R. Guigourès · M. com M. com F. fr © Springer International Publishing Switzerland 2016 F. Guillet et al. K. El Mahrsi et al. this kind of solutions is partial and incomplete which complicates the application of data mining tasks that aim to extract meaningful knowledge about flow dynamics and mobility patterns.

Related work is briefly discussed in Sect. 4. Finally, conclusions and future work are presented in Sect. 5. Co-Clustering Network-Constrained Trajectory Data 21 2 Clustering Approaches In the network-constrained case, trajectories are often modeled using a symbolic data model (Kharrat et al. 2008; Lou et al. 2009; Roh and Hwang 2010). Each trajectory T is represented as a series of succeeding road segments (this is done by applying a mapmatching algorithm, such as Lou et al. (2009), to the original GPS logs).

1), and the automatic categorization of these documents (Sect. 2). We also indicate the evaluation modality of the results generated at these two steps. , medical terms, markers of uncertainty and negation, modifiers, emotions) annotations. Linguistic and semantic annotation is performed through the Ogmios Medical Discourse and Subjectivity 41 platform (Hamon and Nazarenko 2008), that allows to integrate and articulate several Natural Language Processing (NLP) tools, resources and annotation levels.

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Advances in Knowledge Discovery and Management: Volume 5 by Fabrice Guillet, Bruno Pinaud, Gilles Venturini, Djamel Abdelkader Zighed

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