Enhanced Information Retrieval Modelusing Context Based Querying

Traditionally people use libraries for retrieving the information. In recent timesInternet is used for this purpose. Search engines serves as a tool for knowledgehunting from the Internet. Nowadays, these search engines are prone to improve for the following reasons: First the available information is ever growing which leads to vast information and hence prone to contain duplicates also. Secondly, when the query is given by the user to the search engine, it returns a huge number of links from where the user needs to explore and extract the required information. This will lead to waste of time and frustration. To address these problems the proposed system automates the process of extracting useful data from a large pool of search result documents given by search engine as a result of search process on the World Wide Web. When a user initiates a search on the Web, the standard search engines help to find the web documents relevant to it. Our system automatically explores the contents of these search result documents, removes noise, preprocesses the data and extracts the most valuable relevant data. To achieve this rule based algorithms have been developed. This algorithm not only simplifies the search process but also provides just in time information. This is achieved by extracting information based on the context of search. This results in minimal seek time, non-duplicate context based information. The novelty of this system is, it attempts to answer the questions of the user based on the facts extracted from the search result documents.