关键词: 商品匹配, 语义相似度, 本体, 多智能代理, B2B电子商务

Abstract: With the development of B2B E-commerce especially electronic marketplace, enterprises are provided many conveniences and flexibilities for electronic trading. But it brings the problem of information integration due to the heterogeneity of information, which becomes the bottleneck of B2B E-commerce development. The MAS B2B E-commerce model based ontology is introduced, which includes GMAg (Goods Matching Agent) to match goods. By hybrid considering semantic similarity of goods ontology’s part and attributes concept, a Structure semantic Similarity for goods matching is gives, which solves the heterogeneity of information for B2B E-commerce. At last, an instance of automobile proved this algorithm’s accuracy.

Key words: Ontology, Multi-Agents, B2B E-commerce, Goods Matching, Semantic Similarity