Mining Multimedia Documents
Erschienen am 21. April 2017
241 Seiten
978-1-315-39973-7 (ISBN)
Beschreibung
The information age has led to an explosion in the amount of information available to the individual and the means by which it is accessed, stored, viewed, and transferred. In particular, the growth of the internet has led to the creation of huge repositories of multimedia documents in a diverse range of scientific and professional fields, as well as the tools to extract useful knowledge from them.
Mining Multimedia Documents is a must-read for researchers, practitioners, and students working at the intersection of data mining and multimedia applications. It investigates various techniques related to mining multimedia documents based on text, image, and video features. It provides an insight into the open research problems benefitting advanced undergraduates, graduate students, researchers, scientists and practitioners in the fields of medicine, biology, production, education, government, national security and economics.
Mining Multimedia Documents is a must-read for researchers, practitioners, and students working at the intersection of data mining and multimedia applications. It investigates various techniques related to mining multimedia documents based on text, image, and video features. It provides an insight into the open research problems benefitting advanced undergraduates, graduate students, researchers, scientists and practitioners in the fields of medicine, biology, production, education, government, national security and economics.
Weitere Details
Sprache
Englisch
Verlagsort
London
Großbritannien
Verlagsgruppe
Taylor & Francis Ltd
Zielgruppe
Für höhere Schule und Studium
Illustrationen
67 s/w Abbildungen, 17 s/w Tabellen, 31 s/w Photographien bzw. Rasterbilder, 37 s/w Zeichnungen
17 Tables, black and white; 37 Line drawings, black and white; 31 Halftones, black and white; 67 Illustrations, black and white
Dateigröße
10,81 MB
ISBN-13
978-1-315-39973-7 (9781315399737)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Klassifikation
Weitere Ausgaben
Personen
Wahiba Ben Abdessalem Karaa is a professor in the Department of Computer and Information Science at the University of Tunis. She obtained her PhD from Paris 7 Jussieu, France. Her research interests include natural language processing, text mining, image mining, and data mining. She is a member of the editorial board of the several International journals and is the editor-in-chief of the International Journal of Image Mining.
Nilanjan Dey is a professor in the Department of Information Technology in Techno India College of Technology, Kolkata. He is the Editor-in-Chief of International Journal of Ambient Computing and Intelligence, International Journal of Rough Sets and Data Analysis, and Series Editor of the Advances in Geospatial Technologies Book Series. His research interests include medical imaging, soft computing, data mining, machine learning, rough set, mathematical modelling and computer simulation, and the modelling of biomedical systems.
Nilanjan Dey is a professor in the Department of Information Technology in Techno India College of Technology, Kolkata. He is the Editor-in-Chief of International Journal of Ambient Computing and Intelligence, International Journal of Rough Sets and Data Analysis, and Series Editor of the Advances in Geospatial Technologies Book Series. His research interests include medical imaging, soft computing, data mining, machine learning, rough set, mathematical modelling and computer simulation, and the modelling of biomedical systems.
Inhalt
Mining Multimedia Documents: An Overview. Fuzzy Decision Trees for Text Document Clustering. Towards Modeling Semi-Automatic Data Warehouses: Guided by Social Interactions. Multi-Agent System for Text Mining. The transformation of User Requirements in UML Diagrams: An Overview. An Overview of Information Extraction using Textual Case-Based Reasoning. Opinions Classification. Documents Classification Based on Text and Image Features. Content-Based Image Retrieval (CBIR). Mining Knowledge in Medical Image Databases. Segmentation for Medical Image Mining. Biological Data Mining: Techniques and Applications. Video Text Extraction and Mining. Recent Advancement in Multimedia Content using Deep Learning.
