We consider the problem of partitioning, in a highly accurate and highly efficient way, a set of n documents lying in a metric space into k non-overlapping clusters. We augment th...
Filippo Geraci, Marco Pellegrini, Paolo Pisati, Fa...
: This work focuses on clustering a site into groups of documents that are predictive of future user accesses. Two approaches have been developed and tested. The first approach use...
Due to resource constraints, search engines usually have difficulties keeping the local database completely synchronized with the Web. To detect as many changes as possible, the ...
Qingzhao Tan, Ziming Zhuang, Prasenjit Mitra, C. L...
Web mining - data mining for web data - is a key factor of web technologies. Especially, web behavior mining has attracted a great deal of attention recently. Behavior mining invo...
This paper is to investigate the group behavior patterns of search activities based on Web search history data, i.e., clickthrough data, to boost search performance. We propose a ...