关键词: 领域本体, 案例推理, 智能推荐, 语义相似度, 电子商务

Abstract: In view of the shortcomings of the traditional e-commerce recommendation algorithm, the case retrieval algorithm of synthetic semantic similarity was developed in this paper. Through the concept semantic similarity of weighted average commodity, type-based attribute semantic similarity and data-based type attribute value similarity, the comprehensive similarity of the case was calculated. The proposed algorithm solved the problem of low efficiency and inferior precision that calculating the similarity only depended on the attribute value and did not consider semantic and attribute type influence in the traditional recommendation algorithm. The e-commerce intelligence recommendation system framework was designed based on domain ontology cooperated with case reasoning. Through extracting the semantic essential factor in the commercial domain ontology to express the case, the case solution space was opened up to assist user retrieval and complete the commodity recommendation. The experimental results prove that this algorithm is effective and accurate.

Key words: domain ontology, case reasoning, intelligence recommendation, semantic similarity, e-commerce