Research on Concept Clustering of Order Task Ontology based on Modified PART
Clustering is the foundation of establishing the semantic model of order task ontology. The process of concept clustering of order manufacturing task was analyzed to solve the clustering problem. A three-index evaluation method of order task document was proposed to construct the corpus. And then SVD approach was employed to reduce the term-document matrix. On the basis of this, a modified PART clustering algorithm was proposed to reestablish similarity check function by integrating of latent semantic information of ontology concept to improve the clustering accuracy. Finally, the task documents in a building materials equipment enterprise were collected as sample data and the experiment was simulated by matlab. By comparison with ART and PART, the modified PART had better performances in recall and accuracy of concept clustering.