Research on Column Concept Vector Based Web Table Matching

The Web consists of a huge number of structured data in the form of tables, which makes automatically integrating information from those tables of interest to ordinary users possible. A key problem of web table integration is the discovery of correspondences between web table columns. Most of traditional schema matching techniques can't work well because of the lack of schema information and the small number of instance in the web tables. This paper presents a method of web table matching which is based on column concept vector. Column Heading Matcher and Instance Matcher are employed to enhance the matching accuracy. A set of experiments are applied to real-world web tables and the results demonstrate that our method has higher precision and accuracy.