2011 · 26 citations · 20 references
EngineeringExploratory SearchSearch TasksInteractive SearchSearch CasesText MiningInformation RetrievalData ScienceData MiningData ManagementSearch TechnologyKnowledge DiscoveryUser ExperienceComputer ScienceInformation ManagementQuery AnalysisExploratory Search TasksHuman-computer InteractionInteractive Information Retrieval
In this paper, we focus on a specific class of search cases: exploratory search tasks. To describe and quantify their complexity, we present a new methodology and corresponding tools to evaluate the user behavior when carrying out exploratory search tasks. These tools consist of a client called Search-Logger, and a server side database with frontend and an analysis environment. The client is a plug-in for Firefox web browsers. The assembly of the Search-Logger tools can be used to carry out user studies for search tasks independent of a laboratory environment. It collects implicit user information by logging a number of significant user events. Explicit information is gathered via user feedback in the form of questionnaires before and after each search task. We also present the results of a pilot user study. Some of our main observations are: When carrying out exploratory search tasks, classic search engines are mainly used as an entrance point to the web. Subsequently users work with several search systems in parallel, they have multiple browser tabs open and frequently use the clipboard to memorize, analyze and synthesize potentially useful data and information. Exploratory search tasks typically consist of various sessions and can span from hours up to weeks.
20
Gary Marchionini · Communications of the ACM · 2006 · 1.4K citations
Mark Claypool, Phong Le, Makoto Wased et al. · 2001 · 671 citations
Evaluating implicit measures to improve web search
Steve Fox, Kuldeep Karnawat, Mark Mydland et al. · ACM Transactions on Information Systems · 2005 · 564 citations