Combining ontologies and agents to help in solving the heterogeneity problem in e-commerce negotiations

Abstract

Online e-commerce marketplaces for buying and selling products are omnipresent and bring together several suppliers and buyers. Each supplier and buyer has its own format, concepts and characteristics to represent products. Even if both supplier and buyer use an ontology, they may use ontologies that differ significantly either syntactically or semantically. This paper combines the use of ontologies and agent technologies to help in solving the semantic heterogeneity problem in e-commerce negotiations. Thereby, the focus is on ontologies, whose specifications include a concept (item/product), its characteristics (attributes) with the correspondent data types, a natural language description explaining the meaning of the concept, and a set of relationships among these concepts. Our approach aims at creating a methodology that assesses lexical and semantic similarity among concepts represented in different ontologies without the need to build an a priori shared ontology. The lexical measures are used to compare attributes and relations between concepts. We have classified attributes according to their data value types and considered the relation has-part. For the final validation, we are proposing to use the WordNet-based semantic similarity measure between concept names and between their correspondent descriptions.