Personalized Recommendation Method of E-commerce Based on Fusion Technology of Smart Ontology and Big Data Mining

E-commerce personalized recommendation system needs to be able to respond to user page requests in real time and provide recommendation services for users according to different recommendation models chosen by users. In this paper, based on the fusion method of intelligent ontology and big data mining, the semantic access preference of the user is captured by the user interest acquisition algorithm of the semantic cluster, and the current session of the user is matched with the acquired user preference to obtain the recommendation set. The paper presents personalized recommendation method of E-commerce based on fusion technology of smart ontology and big data mining.