User Intended Context Sensitive Mining Algorithm for Search String Composition

With ever growing data on Internet, use of search engines has increased tremendously to find information. It is experienced that current search engines give many irrelevant and redundant results for a query. Redundancy and irrelevance can be reduced by using user intent based context while composing a search string query. This research proposes an algorithm to improve the prediction of search string using context based on User Intent. User profiles are used in the experiment as one of the ways to predict the user intention. Context is chosen and added so as to optimize the keystroke saving while predicting the search string. Autocompleting queries have been attempted by search engines but making it more relevant by adding context is essential.