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Advances in knowledge discovery and ...

Pinaud, Bruno.

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Advances in knowledge discovery and management.. Volume 8

Record Type:	Electronic resources : Monograph/item
Title/Author:	Advances in knowledge discovery and management./ edited by Bruno Pinaud ... [et al.].
other author:	Pinaud, Bruno.
Published:	Cham :Springer International Publishing : : 2019.,
Description:	xviii, 183 p. :ill., digital ;24 cm.
[NT 15003449]:	Part I: Clustering -- Chapter 1. Model based co-clustering of mixed numerical and binary data -- Chapter 2. Co-clustering based exploratory analysis of mixed-type data tables -- Part II: Textual Data -- Chapter 3. Automatically selecting complementary vector representations for semantic textual similarity, etc.
Contained By:	Springer eBooks
Subject:	Data mining - Congresses. -
Online resource:	https://doi.org/10.1007/978-3-030-18129-1
ISBN:	9783030181291

Advances in knowledge discovery and management.. Volume 8
Advances in knowledge discovery and management.Volume 8[electronic resource] /edited by Bruno Pinaud ... [et al.]. - Cham :Springer International Publishing :2019. - xviii, 183 p. :ill., digital ;24 cm. - Studies in computational intelligence,v.8341860-949X ;. - Studies in computational intelligence ;v.834..

Part I: Clustering -- Chapter 1. Model based co-clustering of mixed numerical and binary data -- Chapter 2. Co-clustering based exploratory analysis of mixed-type data tables -- Part II: Textual Data -- Chapter 3. Automatically selecting complementary vector representations for semantic textual similarity, etc.

This book highlights novel research in Knowledge Discovery and Management (KDM), gathering the extended, peer-reviewed versions of outstanding papers presented at the annual conferences EGC'2017 & EGC'2018. The EGC conference cycle was founded by the International French-speaking EGC society ("Extraction et Gestion des Connaissances") in 2003, and has since become a respected fixture among the French-speaking community. In addition to the annual conference, the society organizes various other events in order to promote exchanges between researchers and companies concerned with KDM and its applications to business, administration, industry and public organizations. Addressing novel research in data science, semantic Web, clustering, and classification, the content presented here will chiefly benefit researchers interested in these fields, including Ph.D./M.Sc. students, at public and private laboratories alike.

ISBN: 9783030181291

Standard No.: 10.1007/978-3-030-18129-1doiSubjects--Topical Terms:

551626
Data mining
--Congresses.

LC Class. No.: QA76.9.D343 / A335 2019

Dewey Class. No.: 006.312

Advances in knowledge discovery and management.. Volume 8
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245 0 0 $a Advances in knowledge discovery and management. $n Volume 8 $h [electronic resource] / $c edited by Bruno Pinaud ... [et al.].
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2019.
300 $a xviii, 183 p. : $b ill., digital ; $c 24 cm.
490 1 $a Studies in computational intelligence, $x 1860-949X ; $v v.834
505 0 $a Part I: Clustering -- Chapter 1. Model based co-clustering of mixed numerical and binary data -- Chapter 2. Co-clustering based exploratory analysis of mixed-type data tables -- Part II: Textual Data -- Chapter 3. Automatically selecting complementary vector representations for semantic textual similarity, etc.
520 $a This book highlights novel research in Knowledge Discovery and Management (KDM), gathering the extended, peer-reviewed versions of outstanding papers presented at the annual conferences EGC'2017 & EGC'2018. The EGC conference cycle was founded by the International French-speaking EGC society ("Extraction et Gestion des Connaissances") in 2003, and has since become a respected fixture among the French-speaking community. In addition to the annual conference, the society organizes various other events in order to promote exchanges between researchers and companies concerned with KDM and its applications to business, administration, industry and public organizations. Addressing novel research in data science, semantic Web, clustering, and classification, the content presented here will chiefly benefit researchers interested in these fields, including Ph.D./M.Sc. students, at public and private laboratories alike.
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950 $a Intelligent Technologies and Robotics (Springer-42732)