Because of the rapid development of Information and network technology, Internet has become the largest body of information. The progress of technology and the explosion in the number of users, so there are produced tens of thousands pages every day. Internet has become the largest source of information. In the information explosion times, searching specific topic data in such a huge data is becoming an important topic. For this reason, this paper presents a Game-theoRy-based Algorithm for extracting theme-Block from a web page(GRAB). It can automatically identify user interested topic blocks, and then converted to easy storage, retrieval and analysis of structured data for providing different platforms (eg. mobile phone, PDA) to facilitate the application. This paper provides a prototype system based on GRAB algorithm. I design two experiments, and verify the effectiveness of algorithms through the actual web page data. The first experiment results prove that GRAB algorithm in ten topics of HTML web page can achieve 70% to 90% accuracy rate, especially in news web page. The second experiment selects the best three topics from the first experiment results for data sets, and compare with three existing web blocks retrieving methods. The results prove GRAB overall performance is better than three existing methods. Although processing structured web performance is similar to existing methods, but news web performance is better than existing methods. Processing unstructured web performance is can achieve 87% to 95% accuracy rate, and all is better than three existing web blocks retrieving methods