As with every major intellectual effort, there is a story behind this work as well.

Following four years of education in Computer Science at the Eửtvửs Lorỏnd Tudomỏny Egyetem (ELTE) in Budapest and a year at the Vrije Universiteit in Amsterdam (VUA), just like my peers, I had the obligation to complete a thesis work for a Master's degree in Computer Science. Unlike my peers, however, I was not only looking for a topic, but planned to find a related internship as well: I considered that a guarantee that the topic I chose would have a practical value beyond an exercise per se.

In my quest I had the fortune to meet Frank van Harmelen from the Artificial Intelligence Department of the VUA. He not only offered me a topic and an internship to go with it, but also helped me to joining one of the most reputable research collaboration in the field of Semantic Web [29] technologies and applications. He also introduced me to Hans Akkermans from the Business Informatics Department of the VUA who helped as an advisor during my work. I started in January 2002 at EnerSearch, a Swedish case study partner in the On-To-Knowledge research project. In order to avoid relocation, AIdministrator (another partner in the project) generously hosted me for the duration of my work.

For the following six month I had been vested the responsibility to assemble the components developed in the project into a comprehensive solution for EnerSearch. With very few experience available to build on, my task was rightfully expected to be a challenge and an immense learning endeavor. While strenuous at times and fun at others, it altogether gave me a unique insight into some of the most exciting technologies in AI today and provided the wealth of experience that is captured in the following thesis.

reface

Introduction

1. Ontology

2. Ontology languages

3. The On-To-Knowledge Research Project

3.6. Ontology-based search and knowledge sharing

4. The enerseach case study

5. The First Step: Ontology Engineering

6. The Second Step: Ontology storage, query and transformation

7. The Third Step: Ontology-based Information Retrieval

8. Summary and Conclusion