Research on parallel frequent pattern mining based on ontology and rules

Abstract

After ten years of development, ILP has been widely used in the field of data mining, it is also a hot topic in today's research. But ILP also has many disadvantages, such as it is a NP problem, but also a stand-alone algorithm, so that when the data is large, the efficiency is relatively low. To solve this problem, in this article, the new expression of frequent patterns as well as the heterogeneous knowledge base depending on ontology and knowledge are proposed. Based on the above two improvements, the parallel implementation of ILP can be realized.