Web searching on the Vivisimo search engine

Sherry Koshman, Amanda Spink, Bernard Jansen

Research output: Contribution to journalArticle

60 Citations (Scopus)


The application of clustering to Web search engine technology is a novel approach that offers structure to the information deluge often faced by Web searchers. Clustering methods have been well studied in research labs; however, real user searching with clustering systems in operational Web environments is not well understood. This article reports on results from a transaction log analysis of Vivisimo.com, which is a Web meta-search engine that dynamically clusters users' search results. A transaction log analysis was conducted on 2-week's worth of data collected from March 28 to April 4 and April 25 to May 2,2004, representing 100% of site traffic during these periods and 2,029,734 queries overall. The results show that the highest percentage of queries contained two terms. The highest percentage of search sessions contained one query and was less than 1 minute in duration. Almost half of user interactions with clusters consisted of displaying a cluster's result set, and a small percentage of interactions showed cluster tree expansion. Findings show that 11.1% of search sessions were multitasking searches, and there are a broad variety of search topics in multitasking search sessions. Other searching interactions and statistics on repeat users of the search engine are reported. These results provide insights into search characteristics with a cluster-based Web search engine and extend research into Web searching trends.

Original languageEnglish
Pages (from-to)1875-1887
Number of pages13
JournalJournal of the American Society for Information Science and Technology
Issue number14
Publication statusPublished - Dec 2006
Externally publishedYes


ASJC Scopus subject areas

  • Information Systems
  • Library and Information Sciences

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