Context Based Relevance Evaluation of Web Documents

Focused crawling is considered to be an important strategy to reduce search space and give more relevant links to a user, based on search queries. Existing web crawlers work only on the basis of full string matching of query keywords with words present in various tags or fields in the web pages. But a particular keyword can have different meanings in different contexts depending on its usage as verb, noun etc. For example fly refers to an insect if used as a noun and refers to an act of moving in the air if used as a verb. Most of the existing search engines work on semantic context, based on string matching of keywords but not based on contextual senses of keywords. Further, general crawling strategy of various crawlers is forward oriented, giving less consideration to the backward links of the page. There is a strong need to work on a crawling strategy that overcomes these gaps. In this paper a mechanism that evaluates the web document on the basis of contextual senses (verb, noun etc.) of the keywords contained in the downloaded page is being proposed. Moreover back-link to a web page has also been analyzed with reference to a specific page providing links related to the page. Consequently, more number of relevant links related to one topic is displayed to the user.