Knowledge-driven multimedia information extraction and ontology evolution :
General Material Designation
[Book]
Other Title Information
bridging the semantic gap /
First Statement of Responsibility
Georgios Paliouras, Constantine D. Spyropoulos, George Tsatsaronis (Eds.)
PHYSICAL DESCRIPTION
Specific Material Designation and Extent of Item
1 online resource (ix, 243 pages) :
Other Physical Details
color illustrations, color maps
SERIES
Series Title
Lecture notes in artificial intelligence
Series Title
LNCS sublibrary. SL 7, Artificial intelligence
Series Title
State-of-the-art survey
Volume Designation
6050.
ISSN of Series
0302-9743 ;
INTERNAL BIBLIOGRAPHIES/INDEXES NOTE
Text of Note
Includes bibliographical references and indexes
CONTENTS NOTE
Text of Note
Bootstrapping Ontology Evolution with Multimedia Information Extraction -- Semantic Representation of Multimedia Content -- Semantics Extraction from Images -- Ontology Based Information Extraction from Text -- Logical Formalization of Multimedia Interpretation -- Ontology Population and Enrichment: State of the Art -- Ontology and Instance Matching -- A Survey of Semantic Image and Video Annotation Tools
0
SUMMARY OR ABSTRACT
Text of Note
This book aims to cover the state of the art in the fields of ontology evolution and information extraction from multimedia, while also promoting the synergy between these two fields. The contents stem largely from the research work conducted over a period of three years under the framework of the research project BOEMIE (Bootstrapping Ontology Evolution with Multimedia Information Extraction). The book is designed to provide researchers, practitioners, and students with basic knowledge and skills presenting a sound theoretical framework as well as concrete examples of applications. The book is organized in eight chapters. The first chapter provides an overview of the BOEMIE project and its main achievements. The second chapter presents current approaches to the representation of knowledge about multimedia using ontologies. The following two chapters provide the state of the art in extraction methods for two important types of multimedia content, id est image and text. The fifth chapter covers the automated reasoning process, where the authors attempt to bridge content and knowledge in a process inspired by human reasoning based on perception. The next two chapters provide the state of the art in ontology learning, population and matching, while the last chapter gives a survey of tools that are useful for the annotation of multimedia content with semantics, id est concepts and relations that have a particular meaning in the application domainches
OTHER EDITION IN ANOTHER MEDIUM
Title
Knowledge-driven Multimedia Information Extraction and Ontology Evolution.