Advances in Knowledge Discovery and Management

Volume 8
1. Auflage 2019
ISBN: 978-3-030-18128-4
Verlag: Springer International Publishing

Buch, Englisch, Band 834, 183 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 477 g

Reihe: Studies in Computational Intelligence

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.

Zielgruppe

Research

Autoren/Hrsg.

Pinaud, Bruno

Largeron, Christine

Guillet, Fabrice

Gandon, Fabien

Fachgebiete

• Wirtschaftswissenschaften Betriebswirtschaft Management Wissensmanagement
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Wissensbasierte Systeme, Expertensysteme

Inhaltsverzeichnis

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.