Abstract: In today’s competitive world it is not affordable for any website to lose users due to the bombardment of the advertisements which are irrelevant and of absolutely no use to the customer. The user will only find the advertisements worthy of his attention if they promote the products for which the user has some personal interest or affinity. So it’s the need of the hour to personalize the scheduling of ads for different users with objective to maximize the revenue of the website.
Phase 1 Creation of Repository : Repository will be created for all the customers and in that repository users will be classified according to certain characteristics (likes and dislikes) .It will prepare distinguished databases for each user group based on user click behavior.
This project aims to create an add-on which records user history to identify their preferences and using their data creates a cookie with which browser can interact.Currently only google does this for its product but we want to create general application.
Phase 2 Automatic Query generation: when the user opens a website it will first send a query to the repository to find out users past behavior. The repository will then analyze the query and send a response to the website.
Phase 3 Provide Relevant responses:From this response website will understand user preferences and the website will only send relevant ads to the user .if the website doesn’t have the ads of user interest then it will send ads which are similar to the users interest this is semantics.