Nowadays, many users use web search engines to find and gather information. User faces an increasing amount of various semi-structured information sources. The issue of correlating, integrating and presenting related information to users becomes important. When a user uses a search engine such as Yahoo and Google to seek a specific information, the results are not only information about the availability of the desired information, but also information about other pages on which the desired information is mentioned The number of selected pages is enormous. Therefore, the performance capabilities, the overlap among results for the same queries and limitations of web search engines are an important and large area of research. Extracting information from the web data sources also becomes very important because the massive and increasing amount of diverse semi-structured information sources in the Internet that are available to users, and the variety of web pages making the process of information extraction from web a challenging problem. It is more challenging when an extracted information which is relevant to a user might not be relevant to other users. Thus, an information extraction that considers user's context more specifically user preferences would provide better results to the user. Thus, this paper proposed a framework for extracting information from semi-structured web pages by considering user's context.
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