An effective approach for personalized web search based on community-cluster analysis

Abstract

The concept of Personalized Web Search is commonly used for improving the quality of web search results by identifying and facilitating different users' search needs. There are several techniques such as user profiling, content analysis, hyperlink analysis and biased PageRank algorithm that are used to achieve web personalization. User Profiling is one of the widely used techniques for personalizing web search at large scale. But it contains several technical and ethical issues such as privacy violations, inefficient use of computing resources as well. Collaborative web search is also a kind of a relatively "new concept which defines the way of optimizing/personalizing search results by using details of group of people and contributing the knowledge of all of them about web search. This paper presents the details of an alternative approach for personalizing web results by using user profiling technique with community cluster analysis of collaborative web search by adapting concept of reusability 'among web results.