Improving Search Results Based on Users' Browsing Behavior Using Apriori Algorithm

World Wide Web (WWW) is decentralized, dynamic, and diverse. It is growing exponentially in size. To improve search results, various ranking methods are being used. Due to vast information on the Web, there is a need to build an intelligent technique that automatically evaluates Web pages that are of user interest. In this paper, interest of a user in a particular Web page can be estimated by his browsing behavior without incurring additional time and effort by the user. It can also adapt to changes in user's interests over time. A page ranking mechanism is being proposed which takes user's actions into account. For this, a Web browser has been developed to store user's behavior. Apriori algorithm is applied on the data collected by Web browser which results in most frequent actions out of all actions. A calculated confidence value has been used to calculate weight of the Web page. Higher the weight, higher the rank.