Extracting Textual Information from Google Using Wrapper Class

In general, the web text documents are often structured, un-structured, or semi-structured format that is promptly growing everyday with massive amounts of data. The users provided with many tools for searching relevant information. Some of the searches include, Keyword searching, topic and subject browsing can help users to find relevant information quickly. In addition, Index search mechanisms allow the user to retrieve a set of relevant documents. Occasionally these search mechanisms are not sufficient. With the rapid development of Internet, amount of data available on the web regularly increased, which makes it difficult for humans to distinguish relevant information. A wrapper class is proposed to extract the relevant text information and focus on finding useful facts of knowledge from unstructured web documents using Google. Techniques from information retrieval (IR), information extraction (IE), and pattern recognition are explored.