-
Griesdorf, H.; Spink, A.: Median measure : an approach to IR systems evaluation (2001)
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- Source
- Information processing and management. 37(2001) no.6, S.843-857
-
Spink, A.; Greisdorf, H.: Partial relevance judgements and changes in users information problems during online searching (1997)
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- Pages
- S.323-334
-
Zhang, Y.; Jansen, B.J.; Spink, A.: Identification of factors predicting clickthrough in Web searching using neural network analysis (2009)
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- Date
- 22. 3.2009 17:49:11
- Source
- Journal of the American Society for Information Science and Technology. 60(2009) no.3, S.557-570
-
Spink, A.; Cole, C.: ¬A multitasking framework for cognitive information retrieval (2005)
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- Abstract
- Information retrieval (IR) research has developed considerably since the 1950's to include consideration of more cognitive, interactive and iterative processes during the interaction between humans and IR or Web systems (Ingwersen, 1992, 1996). Interactive search sessions by humans with IR systems have been depicted as interactive IR models (Saracevic, 1997). Human-IR system interaction is also modeled as taking place within the context of broader human information behavior (HIB) processes (Spink et al., 2002). Research into the human or cognitive (user modeling) aspects of IR is a growing body of research on user interactivity, task performance and measures for observing user interactivity. The task context and situational characteristics of users' searches and evaluation have also been identified as key elements in a user's interaction with an IR system (Cool and Spink, 2002; Vakkari, 2003). Major theorized interactive IR models have been proposed relating to the single search episode, including Ingwersen's (1992,1996) Cognitive Model of IR Interaction, Belkin et al.'s (1995) Episodic Interaction Model, and Saracevic's (1996,1997) Stratified Model of IR Interaction. In this chapter we examine Saracevic's Stratified Model of IR Interaction and extend the model within the framework of cognitive IR (CIR) to depict CIR as a multitasking process. This chapter provides a new direction for CIR research by conceptualizing IR with a multitasking context. The next section of the chapter defines the concept of multitasking in the cognitive sciences and Section 3 discusses the emerging understanding of multitasking information behavior. In Section 4, cognitive IR is depicted within a multitasking framework using Saracevic's (1996, 1997) Stratified Model of IR Interaction. In Section 5, we link information searching and seeking models together, via Saracevic's Stratified Model of IR Interaction, but starting with a unitask model of HIB. We begin to model multitasking in cognitive IR in Section 6. In Sections 7 and 8, we increase the complexity of our developing multitasking model of cognitive IR by adding coordinating mechanisms, including feedback loops. Finally, in Section 9, we conclude the chapter and indicate future directions for further research.
- Date
- 19. 1.2007 12:55:22
- Pages
- S.99-112
-
Spink, A.; Greisdorf, H.: Users' partial relevance judgements during online searching (1997)
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- Source
- Online and CD-ROM review. 21(1997) no.5, S.271-280
-
Spink, A.; Greisdorf, H.: Regions and levels : Measuring and mapping users' relevance judgements (2001)
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- Source
- Journal of the American Society for Information Science and technology. 52(2001) no.2, S.161-173
-
Jansen, B.J.; Spink, A.: ¬An analysis of Web searching by European Allthe Web.com users (2005)
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- Abstract
- The Web has become a worldwide source of information and a mainstream business tool. It is changing the way people conduct the daily business of their lives. As these changes are occurring, we need to understand what Web searching trends are emerging within the various global regions. What are the regional differences and trends in Web searching, if any? What is the effectiveness of Web search engines as providers of information? As part of a body of research studying these questions, we have analyzed two data sets collected from queries by mainly European users submitted to AlltheWeb.com on 6 February 2001 and 28 May 2002. AlltheWeb.com is a major and highly rated European search engine. Each data set contains approximately a million queries submitted by over 200,000 users and spans a 24-h period. This longitudinal benchmark study shows that European Web searching is evolving in certain directions. There was some decline in query length, with extremely simple queries. European search topics are broadening, with a notable percentage decline in sexual and pornographic searching. The majority of Web searchers view fewer than five Web documents, spending only seconds on a Web document. Approximately 50% of the Web documents viewed by these European users were topically relevant. We discuss the implications for Web information systems and information content providers.
- Source
- Information processing and management. 41(2005) no.2, S.361-382
-
Spink, A.: Information behavior : an evolutionary instinct (2010)
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- Footnote
- Rez. in: iwp 62(2011) H.1, S.48 (D. Lewandowski): "... Es ist sehr schade, dass die Autorin aus diesem interessanten und für die Zukunft des Fachs sicherlich entscheidenden Thema nicht mehr gemacht hat. Gerade bei einem Thema, das noch nicht intensiv beackert wurde, ist eine ausführliche Darstellung von großer Bedeutung. Auch in Hinblick auf die Unmenge an Literatur, die in diesem Buch zitiert wird, erscheint die Form der Darstellung in keiner Weise angemessen. Ebenso unangemessen wirkt der Preis von 85 Euro für dieses schmale Werk, welches auch gut in der Form von einem oder zwei längeren Aufsätzen hätte veröffentlicht werden können."
- Pages
- XXVIII, 85 S
-
Spink, A.; Jansen, B.J.: Web searching : public searching of the Web (2004)
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- 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.
- Pages
- XIII, 199 S
-
Khopkar, Y.; Spink, A.; Giles, C.L.; Shah, P.; Debnath, S.: Search engine personalization : An exploratory study (2003)
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-
Spink, A.: Information and a sustainable future (1995)
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- Source
- Libri. 45(1995) nos.3/4, S.203-208
-
Wolfram, D.; Spink, A.; Jansen, B.J.; Saracevic, T.: Vox populi : the public searching of the Web (2001)
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- Source
- Journal of the American Society for Information Science and technology. 52(2001) no.12, S.1073-1074
-
Jansen, B.J.; Spink, A.; Saracevic, T.: Real life, real users and real needs : a study and analysis of users queries on the Web (2000)
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- Source
- Information processing and management. 36(2000) no.2, S.207-227
-
Spink, A.: Interactive information seeking and retrieving : a third feedback framework (1996)
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- Pages
- S.10-15
- Source
- Global complexity: information, chaos and control. Proceedings of the 59th Annual Meeting of the American Society for Information Science, ASIS'96, Baltimore, Maryland, 21-24 Oct 1996. Ed.: S. Hardin
-
Ozmutlu, S.; Spink, A.; Ozmutlu, H.C.: ¬A day in the life of Web searching : an exploratory study (2004)
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- Information processing and management. 40(2004) no.2, S.319-345
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He, S.; Spink, A.: ¬A comparison of foreign authorship distribution in JASIST and the Journal of Documentation (2002)
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- Journal of the American Society for Information Science and Technology. 53(2002) no.11, S.953-959
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Ozmutlu, S.; Spink, A.; Ozmutlu, H.C.: Multimedia Web searching trends : 1997-2001 (2003)
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- Information processing and management. 39(2003) no.4, S.611-621
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Spink, A.; Saracevic, T.: Dynamics of search term selection during mediated online searching (1993)
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- Integrating technologies - converging professions: proceedings of the 56th Annual Meeting of the American Society for Information Science, Columbus, OH, 24-28 October 1993. Ed.: S. Bonzi
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Spink, A.; Park, M.; Koshman, S.: Factors affecting assigned information problem ordering during Web search : an exploratory study (2006)
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- Information processing and management. 42(2006) no.5, S.1366-1378
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Spink, A.; Saracevic, T.: Where do the search terms come from? (1992)
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- Pages
- S.363-373
