Optimization of Context Disambiguation in Web Wearch Results

In a knowledge driven economy information plays an important role. Different entities of society are seeking varied information on a day to day basis. In every walk of life decision makers are taking decisions after careful analysis of relevant information. Hence quality of decisions eventually depends upon quality of information. With the advent of Internet technology the population of online information seekers is growing beyond any stretch of imagination. However information which is retrieved from World Wide Web suffers from few drawbacks. One of the major draw backs about which there is a universal concern that is information retrieved is not the same as information perceived. We commonly comes across pages that are not of interest while searching the Web. This is partly due to a word or words in the search query having different contexts, the user obviously expecting to find pages related to the context of interest. This research paper attempts to investigate the usefulness of Web page clustering algorithms to overcome the drawback of mismatching between information desired and information retrieved. This paper also proposes a method to disambiguate contexts in Web search results.