Web searching on the Vivisimo search engine

Abstract

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. presented to the system to determine characteristics of term distribution, queries, and sessions. Sessions on the Vivisimo Web search engine were analyzed further for topic distribution and to examine the degree of multitasking search by typical Web searchers. The overall goal of this research is to understand user interaction with a clustering Web search engine and further extend the line of user interaction research in Web IR.

Collective User Behaviour and Tag Contextualisation in Folksonomies

“…This is a problem quite extensively studied in the literature (e.g. [5,19]) and is also addressed by commercial systems such as Vivisimo [11]. 3 Most existing methods extract keywords from documents and calculate their similarity based on the keywords to obtain a set of clusters.…”

Toward a web search model: Integrating multitasking, cognitive coordination, and cognitive shifts

“…For example, Ozmutlu et al (2003) found that one tenth of Excite users and one third of AlltheWeb.com users conducted multiple-topic searches within a certain session. Koshman, Spink, and Jansen (2006) reported that 11.1% of search sessions over the Vivisimo search engine included a broad variety of search topics. Spink, Park, Jansen, and Pedersen (2006) found that a high degree of multiple topics exist in both two-query sessions (81%) and three or more query sessions (91%) on the AltaVista search engine.…”

Social Computing: The Impact on Cultural Behavior

“…For example, it has been observed that queries placed by users in the United States are likely to contain more operators (include, exclude, wildcard, etc.) than queries placed by users in Europe [53]. Furthermore, culture influences the perception that users develop about systems.…”