Search (66 results, page 1 of 4)

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  1. Branch, J.L.: Investigating the information-seeking process of adolescents : the value of using think alouds and think afters (2000) 0.05
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    Source
    Library and information science research. 22(2000) no.4, S.371-382
  2. Aloteibi, S.; Sanderson, M.: Analyzing geographic query reformulation : an exploratory study (2014) 0.02
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    Date
    26. 1.2014 18:48:22
    Source
    Journal of the Association for Information Science and Technology. 65(2014) no.1, S.13-24
  3. Monchaux, S.; Amadieu, F.; Chevalier, A.; Mariné, C.: Query strategies during information searching : effects of prior domain knowledge and complexity of the information problems to be solved (2015) 0.02
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    Date
    25. 1.2016 18:46:22
    Source
    Information processing and management. 51(2015) no.5, S.557-569
  4. Byström, K.: Information seekers in context : an analysis of the 'doer' in INSU studies (1999) 0.02
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    Date
    22. 3.2002 9:55:52
    Pages
    S.82-95
  5. Ennis, M.; Sutcliffe, A.G.; Watkinson, S.J.: Towards a predictive model of information seeking : empirical studies of end-user-searching (1999) 0.01
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    Date
    22. 3.2002 9:54:13
    Pages
    S.96-115
  6. Pejtersen, A.M.: Investigation of search strategies in fiction based on an analysis of 134 user-librarian conversations (1979) 0.00
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    Pages
    S.107-132
  7. Wildemuth, B.M.; Jacob, E.K.; Fullington, A.;; Bliek, R. de; Friedman, C.P.: ¬A detailed analysis of end-user search behaviours (1991) 0.00
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    Abstract
    Search statements in this revision process can be viewed as a 'move' in the overall search strategy. Very little is known about how end users develop and revise their search strategies. A study was conducted to analyse the moves made in 244 data base searches conducted by 26 medical students at the University of North Carolina at Chapel Hill. Students search INQUIRER, a data base of facts and concepts in microbiology. The searches were conducted during a 3-week period in spring 1990 and were recorded by the INQUIRER system. Each search statement was categorised, using Fidel's online searching moves (S. Online review 9(1985) S.61-74) and Bates' search tactics (s. JASIS 30(1979) S.205-214). Further analyses indicated that the most common moves were Browse/Specity, Select Exhaust, Intersect, and Vary, and that selection of moves varied by student and by problem. Analysis of search tactics (combinations of moves) identified 5 common search approaches. The results of this study have implcations for future research on search behaviours, for thedesign of system interfaces and data base structures, and for the training of end users
    Pages
    S.302-312
  8. Fourie, I.: ¬A theoretical model for studying Web information seeking / searching behaviour (2003) 0.00
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    Pages
    S.169-172
  9. Kim, K.-S.: Effects of emotion control and task on Web searching behavior (2008) 0.00
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    Source
    Information processing and management. 44(2008) no.1, S.373-385
  10. Pu, H.-T.; Chuang, S.-L.; Yang, C.: Subject categorization of query terms for exploring Web users' search interests (2002) 0.00
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    Abstract
    Subject content analysis of Web query terms is essential to understand Web searching interests. Such analysis includes exploring search topics and observing changes in their frequency distributions with time. To provide a basis for in-depth analysis of users' search interests on a larger scale, this article presents a query categorization approach to automatically classifying Web query terms into broad subject categories. Because a query is short in length and simple in structure, its intended subject(s) of search is difficult to judge. Our approach, therefore, combines the search processes of real-world search engines to obtain highly ranked Web documents based on each unknown query term. These documents are used to extract cooccurring terms and to create a feature set. An effective ranking function has also been developed to find the most appropriate categories. Three search engine logs in Taiwan were collected and tested. They contained over 5 million queries from different periods of time. The achieved performance is quite encouraging compared with that of human categorization. The experimental results demonstrate that the approach is efficient in dealing with large numbers of queries and adaptable to the dynamic Web environment. Through good integration of human and machine efforts, the frequency distributions of subject categories in response to changes in users' search interests can be systematically observed in real time. The approach has also shown potential for use in various information retrieval applications, and provides a basis for further Web searching studies.
    Source
    Journal of the American Society for Information Science and technology. 53(2002) no.8, S.617-630
  11. Spink, A.; Park, M.; Koshman, S.: Factors affecting assigned information problem ordering during Web search : an exploratory study (2006) 0.00
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    Source
    Information processing and management. 42(2006) no.5, S.1366-1378
  12. Baruchson-Arbib, S.; Bronstein, J.: Humanists as information users in the digital age : the case of Jewish studies scholars in Israel (2007) 0.00
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    Source
    Journal of the American Society for Information Science and Technology. 58(2007) no.14, S.2269-2279
  13. Tenopir, C.; Nahl-Jakobovits, D.; Howard, D.L.: Strategies and assessments online : novices' experience (1991) 0.00
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    Source
    Library and information science research. 13(1991) no.3, S.237-266
  14. Mann, L.; Ball, C.: ¬The relationship between search strategy and risky choice (1994) 0.00
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    Source
    Australian journal of psychology. 46(1994) no.3, S.131-136
  15. Spink, A.; Ozmutlu, H.C.; Ozmutlu, S.: Multitasking information seeking and searching processes (2002) 0.00
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    Source
    Journal of the American Society for Information Science and technology. 53(2002) no.8, S.639-652
  16. Spink, A.; Danby, S.; Mallan, K.; Butler, C.: Exploring young children's web searching and technoliteracy (2010) 0.00
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    Source
    Journal of documentation. 66(2010) no.2, S.191-206
  17. Xie, I.; Joo, S.: Transitions in search tactics during the Web-based search process (2010) 0.00
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    Source
    Journal of the American Society for Information Science and Technology. 61(2010) no.11, S.2188-2205
  18. DiMartino, D.; Zoe, L.R.: End-user full-text searching : access or excess? (1996) 0.00
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    Source
    Library and information science research. 18(1996) no.2, S.133-149
  19. Spink, A.; Goodrum, A.; Robins, D.: Elicitation behavior during mediated information retrieval (1998) 0.00
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    Source
    Information processing and management. 34(1998) nos.2/3, S.257-273
  20. Wang, P.; Berry, M.W.; Yang, Y.: Mining longitudinal Web queries : trends and patterns (2003) 0.00
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    Source
    Journal of the American Society for Information Science and technology. 54(2003) no.8, S.743-758

Years