Current search engines rely on centralized page ranking algorithms which compute page rank values as single (global) values for each Web page. Recent work on topic-sensitive PageRa...
Paul-Alexandru Chirita, Daniel Olmedilla, Wolfgang...
We study personalized web ranking algorithms based on the existence of document clusterings. Motivated by the topic sensitive page ranking of Haveliwala [19], we develop and imple...
Despite the effectiveness of search engines, the persistently increasing amount of web data continuously obscures the search task. Efforts have thus concentrated on personalized...
We present a new approach for personalizing Web search results to a specific user. Ranking functions for Web search engines are typically trained by machine learning algorithms u...
David Sontag, Kevyn Collins-Thompson, Paul N. Benn...
Internet search engines identify web pages that contain user-specified keywords, and then rank these pages according to their (heuristically assessed) relevance to the user’s qu...