A novel approach of table detection and analysis for semantic annotation
Semantic web mining is getting more attention in intelligent web applications. Many web sites, especially those dynamically generate HTML pages to display the results of user queries, present information in the form of lists or tables. It is very useful to extract concept instances from these tables for many web applications such as intelligent agent systems for on-line product recommendations. This paper describes a technique for extracting data from tables in two steps, namely table detection and table analysis. The table detection step identifies the existence of a table and extracts its contents, and the table analysis step discovers the semantic meanings embedded in the table and associates them with the concepts described in the domain ontology that are used for semantic annotation on these tables. Our algorithm has been tested based on real-life web documents and the experimental results are encouraging.
table detection semantic annotation ontology