CTGE-ILP: Correlative Term Graph-based Extended ILP

摘要：

Now it is much more prevalent to mine complex data in the fields of data mining and the main methods include the experience and technology of no-structer data mining. On account of the flexible practicability and broad appliance of graph theory and technology, the research of graph-based data mining has presently been becoming an important direction in this domain. In this paper, knowledge discovery researching was studyed throgh the technology of correlative graphbased data mining. The concept of CTGE-ILP( Correlative Term Graph-based Extended Inductive Logic Programming) and the correlative term graph were bring forward, and then discussing the reasoning technology by combining correlative term graph theory and inductive logic programming technic. Next we design the technology of refutable consequence in CTGE-ILP and the corresponding algorithm. At last an prototype integrating both the idea and technic above was opened up and turned out its validity via the data demonstration.

作者: Liu Bo

作者单位: College of Educational Information and Technology, South China Normal University,Guangzhou 510631, China

会议类型: 国际会议

会议名称: 2007年第三届语义和知识网格国际会议(Third International Conference on Semantics,Knowledge,and Grid)(SKG 2007)

会议地点: 西安

会议语种:英文

在线出版日期: 2007-10-29（万方平台首次上网日期，不代表论文的发表时间）