Visual Clue Based Extraction of Web Data from Flat and Nested Data Records

This paper studies the problem of identification and extraction of structured data items from the nested and flat records of given web pages. Each of such pages may contain several groups of structured records. Most of the existing methods still have certain limitations. In this paper, we propose a more novel and effective technique for the extraction of data items. Given a page, the proposed technique first identifies the data region based on the visual clue information. It then extracts each record from the data region and identifies it whether it is a flat or nested records based on visual information – the area covered and the number of data items present in each record. The next step is data items extraction from these records and transferring them into the database. Once the data items are present in the database knowledge discovery can be carried out. This technique extracts data items fro the both nested and flat records. Our experimental results show that the proposed technique is effective and better than existing techniques.