Efficient Algorithm for Mining on Bio Medical Data for Ranking the Web Pages

Information in the internet is evolving in terms of high volume through different sources. Extracting tuples from HTML pages has been an important issue in various web applications such as web data integration, e-commerce market monitoring, and mash ups that repurpose and selectively combine existing web data services. Data Mining is the process of analyzing data from different perspectives and summarizing it into useful information. Text Mining uses many applications of Data Mining. Text Mining is the discovery of unknown information by automatically extracting and relating the information from different resources. Text is classified based on the content that is used for mining. It is done based on comparing the text documents with the database. In the existing system, techniques like named entity recognition, information retrieval, information extraction and knowledge discovery are used for text mining. Google used page rank method to retrieve and rank the documents. However, Google rank may not provide the documents with the most relevant information. In the proposed system, information retrieval is used to collect many web documents and pre-processing the web documents and extract the text data. Then a word is identified as bio medical entity or not by using a Database with medical keywords. The page containing more bio medical words is ranked first. More relevant documents can be obtained by re ranking the documents using medical database.