Scalable Semantic Annotation of Text Using Lexical and Web Resources

Abstract. In this paper we are dealing with the task of adding domainspecific semantic tags to a document, based solely on the domain ontology and generic lexical and Web resources. In this manner, we avoid the need for trained domain-specific lexical resources, which hinder the scalability of semantic annotation. More specifically, the proposed method maps the content of the document to concepts of the ontology, using the WordNet lexicon and Wikipedia. The method comprises a novel combination of measures of semantic relatedness and word sense disambiguation techniques, in order to identify the most related ontology concepts for the document. We test the method on two case studies: (a) a set of summaries, accompanying environmental news videos, (b) a set of medtracts. The results in both cases show that the proposed method achieves reasonable performance, thus indicating a promising path for scalable semantic annotation of documents.

• Type: Conference
• Year: 2010
• Where: SETN
• Authors: Elias Zavitsanos, George Tsatsaronis, Iraklis Varlamis, Georgios Paliouras
• Keywords: Artificial Intelligence, Domainspecific Semantic Tags, Semantic, Semantic Annotation, SETN 2010