© 2011

Knowledge-Driven Multimedia Information Extraction and Ontology Evolution

Bridging the Semantic Gap

  • Georgios Paliouras
  • Constantine D. Spyropoulos
  • George Tsatsaronis

Part of the Lecture Notes in Computer Science book series (LNCS, volume 6050)

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 6050)

Table of contents

  1. Front Matter
  2. Georgios Paliouras, Constantine D. Spyropoulos, George Tsatsaronis
    Pages 1-17
  3. Kalliopi Dalakleidi, Stamatia Dasiopoulou, Giorgos Stoilos, Vassilis Tzouvaras, Giorgos Stamou, Yiannis Kompatsiaris
    Pages 18-49
  4. Ioannis Pratikakis, Anastasia Bolovinou, Bassilios Gatos, Stavros Perantonis
    Pages 50-88
  5. Vangelis Karkaletsis, Pavlina Fragkou, Georgios Petasis, Elias Iosif
    Pages 89-109
  6. Sofia Espinosa, Atila Kaya, Ralf Möller
    Pages 110-133
  7. Georgios Petasis, Vangelis Karkaletsis, Georgios Paliouras, Anastasia Krithara, Elias Zavitsanos
    Pages 134-166
  8. Silvana Castano, Alfio Ferrara, Stefano Montanelli, Gaia Varese
    Pages 167-195
  9. Stamatia Dasiopoulou, Eirini Giannakidou, Georgios Litos, Polyxeni Malasioti, Yiannis Kompatsiaris
    Pages 196-239
  10. Back Matter

About this book


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, i.e. 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, i.e. concepts and relations that have a particular meaning in the application domain.


automated reasoning knowledge processing multimedia content analysis ontology learning semantic representation

Editors and affiliations

  • Georgios Paliouras
    • 1
  • Constantine D. Spyropoulos
    • 1
  • George Tsatsaronis
    • 2
  1. 1.Institute of Informatics and TelecommunicationsNational Centre for Scientific Research “Demokritos”Ag. ParaskeviGreece
  2. 2.Biotechnology Center (BIOTEC)TU DresdenDresdenGermany

Bibliographic information