Abstract
With the development and application of e-commerce, the research on enterprise online product recommendation service model under big data background has become a frontier issue. Collaborative filtering algorithm is improved based on domain ontology, which calculates semantic similarity of domain ontology from two angles of hierarchical similarity and attribute similarity. It combines with the traditional grading similarity to dig out semantic relationship between products, and then it draws abstract semantic information. The experiment results show that it can significantly improve the recommendation speed. Besides, recommendation efficiency is also relatively stable. In dealing with large data, computational efficiency is better than the traditional collaborative filtering algorithm, recommendation algorithm based on association rules and recommendation algorithm based on content.
