The tutorial will give an introduction into the field of ontology learning from textual resources. It will assume no prior knowledge of the field and will thus be suited for people with very different backgrounds such as Machine Learning, Natural Language Processing, Information Retrieval, Knowledge Management, Semantic Web, Artificial Intelligence, etc.
After giving a general overview of the field and discussing the main tasks addressed therein, we will focus on the state-of-the-art of the field in the first main part of the tutorial. On the one hand, we will discuss the linguistic aspects related to ontology learning, i.e., the treatment of synonymy, multilingual term variants and relation extraction. Further, we discuss machine learning methods that have been applied to ontology learning tasks before discussing opportunities for combining Natural Language Processing with Machine Learning techniques. Finally, we will focus on the evaluation of ontology learning systems, especially discussing benchmarks and gold standards as well as problems involved in the evaluation of ontology learning systems. In the second part of the tutorial we will focus on the so called knowledge lifecycle and discuss how ontology learning techniques can be included in the knowledge engineering process to provide a benefit. In this part we will also review some of the currently available ontology learning frameworks and systems, discussing their main features as well as drawbacks. Finally, a wrap-up will conclude the tutorial and briefly review the main lessons to be learned from the tutorial.