A Personalized Web Search Based on User Profile and User Clicks
Abstract— A Personalized Web Search Based on User Profile and User Clicks. Generally web search engines are built to serve all users, independent of the individual needs of any user. Personalization of web search is to carry out retrieval for each user incorporating their interest. This has become an important factor in daily usage as it improves the retrieval effectiveness on topics that the user would look for. There are several studies that have been done in this field. This paper proposes a new idea on personalized web search which is based on user profile and user clicks. Function-based personalization is mainly by designing new sorting algorithms or transforming the existing algorithms to achieve the personalized services. The most representations are: Using SVM support vector machine algorithm to sort the results of web pages;  An algorithm called Cube < Final Year Projects 2016 > SVD is used to calculate the relationship among the three-dimensional data <user, query word, page>, then obtains the weight of each page and re-sorts them. In this article, we try to combine content based method and function based method.
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