Record-Level Information Extraction from a Web Page based on Visual Features

Web databases contain a huge amount of structured data which are easily obtained via their query interfaces only. Query results are presented in dynamically generated web pages, usually in the form of data records, for human use. Decisive for web data integration applications is the problem of automatically extracting data records from query result pages, such as comparison shopping sites, meta-search engines, etc. A number of approaches to query result extraction have been proposed. As the structures of web pages become more critical, these approaches start to fail. Query result pages usually also contain other types of information in addition to query results, e.g., advertisements, navigation bar, etc. Most of the existing approaches do not move out such impertinent contents which may affect the accuracy of data record extraction. We have observed that query results are usually displayed in regular visual patterns and terms used in a query often reappear in query results. The paper proposes a novel approach that makes use of visual features and query terms to identify the data section and extract data records from it. this also uses several content and visual features of visual blocks in a data section to filter out noisy blocks. The results of this experiment tests on a large set of query result pages in different domains show that the proposed approach is