Cluster Based Personalized Search

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 implement an efficient “local-cluster” algorithm by extending the web search algorithm of Achlioptas et al. [10]. We propose some formal criteria for evaluating such personalized ranking algorithms and provide some preliminary experiments in support of our analysis.

• Type: Conference
• Year: 2009
• Where: WAW
• Authors: Hyun Chul Lee, Allan Borodin
• Keywords: Algorithms, Personalized Ranking Algorithms, Ranking Algorithms, WAW 2009, Web Ranking Algorithms