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This paper deals with studies the problem of identification and extraction of flat and nested data records from a given web page. With the explosive growth of information sources available on the World Wide Web, it has become increasingly difficult to identify the relevant pieces of information, since web pages are often cluttered with irrelevant content like advertisements, navigation-panels, copyright notices etc., surrounding the main content of the web page. Hence, it is useful to mine such data regions and data records in order to extract information from such web pages to provide value-added services. Currently available automatic techniques to mine data regions and data records from web pages are still unsatisfactory because of their poor performance. In this paper, we propose a new method to identify and extract the data records from the web pages automatically. 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 record based on visual information -- the area covered by and the number of data items present in each record. The experimental results show that the proposed technique is effective and better than existing techniques.