Search (10 results, page 1 of 1)

Ozmutlu, S.; Spink, A.; Ozmutlu, H.C.: ¬A day in the life of Web searching : an exploratory study (2004) 0.03

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Source: Information processing and management. 40(2004) no.2, S.319-345
Year: 2004

Spink, A.; Cole, C.: ¬A human information behavior approach to a philosophy of information (2004) 0.03

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Source: Library trends. 52(2004) no.3, S.617-628
Year: 2004

Spink, A.: Multitasking information behavior and information task switching : an exploratory study (2004) 0.02

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Source: Journal of documentation. 60(2004) no.4, S.336-351
Year: 2004

Spink, A.: Web search : emerging patterns (2004) 0.02

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Source: Library trends. 52(2004) no.2, S.299-306
Year: 2004

Spink, A.; Jansen, B.J.; Pedersen , J.: Searching for people on Web search engines (2004) 0.02

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Source: Journal of documentation. 60(2004) no.3, S.266-278
Year: 2004

Spink, A.; Cole, C.: Introduction (2004) 0.02

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Source: Journal of the American Society for Information Science and Technology. 55(2004) no.9, S.767-768
Year: 2004

Spink, A.; Jansen, B.J.: Web searching : public searching of the Web (2004) 0.01
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Classification

ZA4230.S65 2004

Footnote

Rez. in: Information - Wissenschaft und Praxis 56(2004) H.1, S.61-62 (D. Lewandowski): "Die Autoren des vorliegenden Bandes haben sich in den letzten Jahren durch ihre zahlreichen Veröffentlichungen zum Verhalten von Suchmaschinen-Nutzern einen guten Namen gemacht. Das nun erschienene Buch bietet eine Zusammenfassung der verstreut publizierten Aufsätze und stellt deren Ergebnisse in den Kontext eines umfassenderen Forschungsansatzes. Spink und Jansen verwenden zur Analyse des Nutzungsverhaltens query logs von Suchmaschinen. In diesen werden vom Server Informationen protokolliert, die die Anfragen an diesen Server betreffen. Daten, die aus diesen Dateien gewonnen werden können, sind unter anderem die gestellten Suchanfragen, die Adresse des Rechners, von dem aus die Anfrage gestellt wurde, sowie die aus den Trefferlisten ausgewählten Dokumente. Der klare Vorteil der Analyse von Logfiles liegt in der Möglichkeit, große Datenmengen ohne hohen personellen Aufwand erheben zu können. Die Daten einer Vielzahl anonymer Nutzer können analysiert werden; ohne dass dabei die Datenerhebung das Nutzerverhalten beeinflusst. Dies ist bei Suchmaschinen von besonderer Bedeutung, weil sie im Gegensatz zu den meisten anderen professionellen Information-Retrieval-Systemen nicht nur im beruflichen Kontext, sondern auch (und vor allem) privat genutzt werden. Das Bild des Nutzungsverhaltens wird in Umfragen und Laboruntersuchungen verfälscht, weil Nutzer ihr Anfrageverhalten falsch einschätzen oder aber die Themen ihrer Anfragen nicht nennen möchten. Hier ist vor allem an Suchanfragen, die auf medizinische oder pornographische Inhalte gerichtet sind, zu denken. Die Analyse von Logfiles ist allerdings auch mit Problemen behaftet: So sind nicht alle gewünschten Daten überhaupt in den Logfiles enthalten (es fehlen alle Informationen über den einzelnen Nutzer), es werden keine qualitativen Informationen wie etwa der Grund einer Suche erfasst und die Logfiles sind aufgrund technischer Gegebenheiten teils unvollständig. Die Autoren schließen aus den genannten Vor- und Nachteilen, dass sich Logfiles gut für die Auswertung des Nutzerverhaltens eignen, bei der Auswertung jedoch die Ergebnisse von Untersuchungen, welche andere Methoden verwenden, berücksichtigt werden sollten.

LCC

ZA4230.S65 2004

Year

2004
Koshman, S.; Spink, A.; Jansen, B.J.: Web searching on the Vivisimo search engine (2006) 0.01
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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.

Zhang, Y.; Jansen, B.J.; Spink, A.: Identification of factors predicting clickthrough in Web searching using neural network analysis (2009) 0.01

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Date: 22. 3.2009 17:49:11

Spink, A.; Cole, C.: ¬A multitasking framework for cognitive information retrieval (2005) 0.01

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Date: 19. 1.2007 12:55:22

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