A Methodology for Semantically Annotating a Corpus Using a Domain Ontology and Machine Learning

In this paper we present a methodology for the semantic annotation of domain-specific corpora. This method relies on a domain ontology used initially for identifying and annotating domain- specific instances within the corpus. A machine learning-based information extraction system is then trained on the annotated corpus. The final result of this process is a model which is used to annotate new corpora in the specific domain. We applied the proposed methodology to a Web corpus examining different ontology size using hidden Markov models. The paper presents the proposed methodology together with some first experimental results.