Privacy Based Personalized Web Search

Abstract

Searching is one of the common task performed on the Internet. Search engines are the basic tool of the internet, from where one can collect related information and searched according to the specified keyword given by the user. The information on the web is growing dramatically. The user has to spend more time in the web in order to find the particular information they are interested in. Existing web search engines do not consider particular needs of user and serve each user equally. Moreover it also takes more time in searching a pertinent content. Privacy based Personalized Web Search Engine is considered as a promising solution to handle these problems, since different search results can be provided depending upon the choice and information needs of users. It exploits user information and search context to learning in which sense a query refer. In order to perform Personalized Web search it is important to model User's interest. User profiles are constructed to model user's need based on his/her web usage data. This Enhanced User Profile will help the user to retrieve concentrated information. It can be used for suggesting good web pages to the user based on his/her search query and background knowledge. And also implement the pruning algorithm to eliminate the user details from anonymous person for preserving the key word privacy. User privacy can be provided in the form of protection like without compromising the personalized search quality.