Towards a unified solution: data record region detection and segmentation

Although the task of data record extraction from Web pages has been studied extensively, yet it fails to handle many pages due to their complexity in format or layout. In this paper, we propose a unified method to tackle this task by addressing several key issues in a uniform manner. A new search structure, named as Record Segmentation Tree (RST), is designed, and several efficient search pruning strategies on the RST structure are proposed to identify the records in a given Web page. Another characteristic of our method which is significantly different from previous works is that it can effectively handle complicated and challenging data record regions. It is achieved by generating subtree groups dynamically from the RST structure during the search process. Furthermore, instead of using string edit distance or tree edit distance, we propose a token-based edit distance which takes each DOM node as a basic unit in the cost calculation. Extensive experiments are conducted on four data sets, including flat, nested, and intertwine records. The experimental results demonstrate that our method achieves higher accuracy compared with three state-of-the-art methods.