Journal of Information and Knowledge (Formerly SRELS Journal of Information Management)

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Information Search Patterns in Complex Tasks


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1 Tampere University, FIN - 33014, Finland
     

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This paper seeks to analyze information search process in complex tasks1. Complex tasks are larger tasks, which lead people to engage in search tasks for finding information to advance those tasks. Search process consists of activities from query formulation to working with sources selected for task outcome. This paper approaches task performance from the cognitive point of view conceptualizing it as changes in knowledge structures. These structures consist of concepts and their relations representing some phenomenon. Changes in knowledge structures are associated to query formulation and search tactics, selecting contributing sources and working with sources for creating task outcome. As a result, hypotheses concerning associations between changes in knowledge structures and search behaviors are suggested. The paper also presents some ideas for success indicators at various stages of search processes.

Keywords

Cognitive Search, Information Seeking, Information Search Process, Information User, Search Outcome.
User
About The Author

Pertti Vakkari
Tampere University, FIN - 33014
Finland


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  • Ahn, J.-W., Brusilovsky, P., He, D., Grady, J. and Li, Q. (2008). Personalized web exploration with task models. In Proc WWW 2008 (pp. 1-10). New York, NY: ACM. https://doi.org/10.1145/1367497.1367499

  • Bates M. J. (1979). Information search tactics. Journal of the American Society for Information Science, 30(4), 205-214. https://doi.org/10.1002/asi.4630300406

  • Belkin N.J. (1980). Anomalous states of knowledge as a basis for information retrieval. Canadian Journal of Information and Library Science, 5, 133-143.

  • Belkin, N. J., Cole, M., and Liu, J. (2009). A model for evaluating interactive information retrieval. In SIGIR Workshop on the Future of IR Evaluation, July 23, 2009, Boston.

  • Belkin, N. et al. (2017). 2nd Workshop on Supporting Complex Search Tasks. In Proceedings of CHIIR’17. https://doi.org/10.1145/3020165.3022163

  • Bron M, van Gorp J, Nack F, de Rijke M, Vishneuski A and de Leeuw S. (2012). A subjunctive exploratory search interface to support media studies researchers. In: Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval (SIGIR ‘12) (pp. 425-434). New York, NY: ACM. https://doi.org/10.1145/2348283.2348342

  • Brookes, B. (1980). The foundation of information science. Part I: Philosophical aspects. Journal of Information Science, 2,125-133. https://doi.org/10.1177/016555158000200302

  • Budzik, J. and Hammond, K. (2000). User interactions with everyday applications as context for just-in-time information access. In Proc UIU’00 (pp. 44-51). New York, NY: ACM. https://doi.org/10.1145/325737.325776

  • Butcher KR, Davies S, Crockett A, Dewald A and Zheng R. (2011). Do graphical search interfaces support effective search for and evaluation of digital library resources? In: Proceedings of the 11th annual international ACM/IEEE joint conference on Digital libraries (JCDL ‘11) (pp. 315-324). New York, NY: ACM. https:// doi.org/10.1145/1998076.1998136 PMid:21816928 PMCid:PMC3150100

  • Campbell, D. J. (1988). Task complexity: a review and analysis. Academy of Management Review, 13, 40-52. https://doi.org/10.2307/258353

  • Cho, B.-Y., Woodward, L., Li, D. and Barlow, W. (2017). Examining adolescents’ strategic processing during online reading with a question-generating task. American Educational Research Journal, 54(4): 691-724. https://doi.org/10.3102/0002831217701694

  • Collins-Thompson, K., Rieh, S. Y., Haynes, C. C., Syed, R. (2016). Assessing learning outcomes in web search: A comparison of tasks and query strategies. Proc of the 1st CHIIR Conf (pp. 163-172). https://doiorg/10.1145/2854946.2854972

  • Fox,S., Karnawat, K., Mydland, M., Dumais, S., and White, T. (2005). Evaluating implicit measures to improve web search. ACM TOIS, 23(2), 147-168. https://doi. org/10.1145/1059981.1059982

  • Gwizdka, J. (2014). Characterizing relevance with eye-tracking measures. In Proceedings of the 5th Information Interaction in Context Symposium (pp. 58- 67). ACM. https://doi.org/10.1145/2637002.2637011

  • Hagen, M., Potthast, M., Völske, M., Gomoll, J. and Stein, B. (2016). How Writers Search: Analyzing the Search and Writing Logs of Non-fictional Essays. In Proc CHIIR’16, Diane Kelly, Rob Capra, Nick Belkin, Jaime Teevan, and Pertti Vakkari (Eds.) (pp. 193-202). ACM. https://doi. org/10.1145/2854946.2854969

  • He, D., Brusilovsky, P, Ahn, J., Grady, J., Farzan, R., Peng, Y., Yang, Y., and Rogati, M. (2008). An evaluation of adaptive filtering in the context of realistic task-based information exploration. IP&M, 44, 511-533. https:// doi.org/10.1016/j.ipm.2007.07.009

  • Hersh, W. (2003). Information retrieval: A health and biomedical perspective (2nd ed.). New York: Springer.

  • Hersh, W, Pentecost, J, and Hickam, D. (1996). A taskoriented approach to information retrieval. Journal of the American Society for Information Science, 47(1), 50-56. https://doi.org/10.1002/(SICI)1097- 4571(199601)47:1<50::AID-ASI5>3.0.CO;2-1

  • Ingwersen, P. (1992) Information Retrieval Interaction. London: Taylor Graham.

  • Jarvelin, K., Vakkari, P., Arvola, P., Baskaya, F., Jarvelin, A., Kekalainen, J., Keskustalo, H., Kumpulainen, S., Saastamoinen, M., Savolainen, R., and Sormunen, E. (2015). Task-based information interaction evaluation: The viewpoint of program theory. ACM Trans Inf Syst, 33(1), 3:1-3:30. https://doi.org/10.1145/2699660

  • Kelly, D. and Cool, C. (2002). The effects of topic familiarity on information search behavior. In Proc. JCDL’02. (pp. 74-75). New York, NY: ACM. https://doi. org/10.1145/544220.544232

  • Kong, W. and Allan, J. (2014). Extending faceted search to the general web. In Proc. CIKM’14 (pp. 839-848). New York, NY: ACM. https://doi.org/10.1145/2661829.2661964

  • Kuhlthau C. (1993). Seeking Meaning. Norwood, N.J.: Ablex. Lancaster, W., and Warner, A. (1993). Information retrieval today. Arlington, VA: Information Resources Press.

  • Liu, C., Gwizdka, J., and Liu. J. (2010). Helping identify when users find useful documents: Examination of query reformulation intervals. In Proceedings of IIiX’10 (pp. 215-224). https://doi.org/10.1145/1840784.1840816

  • Liu, C. Belkin, N. J., and Cole, M. J. (2012). Personalization of search results using interaction behaviors in search sessions. In Proc. SIGIR’12. (pp. 205-214). ACM. https:// doi.org/10.1145/2348283.2348314

  • Liu, J., and Belkin, N. J. (2010). Personalizing information retrieval for multi-session tasks: the roles of task stage and task type. In Proc. SIGIR’10 (pp. 26-33). ACM. https://doi.org/10.1145/1835449.1835457

  • Liu, J., and Belkin, N. J. (2012). Searching vs. writing: Factors affecting information use task performance. In Proceedings of the American Society for Information Science and Technology (pp. 1-10). https://doi.org/10.1002/meet.14504901127

  • Liu, J., Belkin, N.J. Zhang, X. and Yuan, X. (2013). Examining users’ knowledge change in the task completion process. IP&M, 49, 1058-1074. https://doi.org/10.1016/j.ipm.2012.08.006

  • Marchionini G. (1995). Information seeking in electronic environments. Cambridge University Press. https://doi.org/10.1017/CBO9780511626388

  • Pennanen M. and Vakkari P. (2003). Students’ conceptual structure, search process and outcome while preparing a research proposal. Journal of the American Society for Information Science and Technology, 54(8), 759-770. https://doi.org/10.1002/asi.10273

  • Qu, Y., and Furnas, G. (2008). Model-driven evaluation of exploratory search: A study under sensemaking framework. Information Processing and Management, 44(2), 534-555. https://doi.org/10.1016/j.ipm.2007.09.006

  • Raman, K., Bennett, P. and Collins-Thompson, K. (2013). Toward whole-session relevance: Exploring intrinsic diversity in web search. In Proc. SIGIR’13. (pp. 463-472). New York, NY: ACM. https://doi.org/10.1145/2484028.2484089

  • Robertson, S. (2001). Problem solving. Hove: Psychology Press. https://doi.org/10.4324/9780203457955_chapter_1

  • Russell, D., Stefik, M., Pirolli, P. and Card, S. (1993). The cost structure of sensemaking. In Proc. CHI ‘93 (pp. 269-276). New York, NY: ACM. https://doi.org/10.1145/169059.169209

  • Serola, S. and Vakkari, P. (2005). The anticipated and assessed contribution of information types in references retrieved for preparing a research proposal. Journal of the American Society for Information Science, 56(4), 373-381. https://doi.org/10.1002/asi.20113

  • Smucker, M. D., and Jethani, C. (2012). Time to judge relevance as an indicator of assessor error. In Proc. SIGIR’12. (pp. 1153-1154). ACM. https://doi.org/10.1145/2348283.2348515

  • Syed, R. and Collins-Thompson, K. (2017). Retrieval algorithms optimized for human learning. In Proc. SIGIR’17 (pp. 555-564). New York, NY: ACM. https://doi.org/10.1145/3077136.3080835

  • Vakkari, P. (1999). Task complexity, problem structure and information actions: integrating studies on information seeking and retrieval. Information Processing and Management, 35(6), 819-837. https://doi.org/10.1016/ S0306-4573(99)00028-X

  • Vakkari, P. (2003) Task-based information searching. ARIST 2003, (pp. 413-464). Medford, NJ: Information Today. https://doi.org/10.1002/aris.1440370110

  • Vakkari, P. (2010). Exploratory searching as conceptual exploration. In: Proceedings of 4th Workshop on Human-Computer Interaction and Information Retrieval (pp. 24-27). New Brunswick, NJ.

  • Vakkari, P. (2016). Searching as Learning. A Systematization based on Literature. Journal of Information Science, 42(1), 7-18. https://doi.org/10.1177/0165551515615833

  • Vakkari, P. (2000). Relevance and contributing information types of searched documents in task performance. In: Proceedings of the 23rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ‘00) (pp. 2-9). New York, NY: ACM. https://doi.org/10.1145/345508.345512

  • Vakkari, P. (2001). A theory of the task-based information retrieval process: A summary and generalization of a longitudinal study. Journal of Documentation, 57(1), 44-60. https://doi.org/10.1108/EUM0000000007075

  • Vakkari, P and Hakala, N. (2000). Changes in relevance criteria and problem stages in task performance. Journal of Documentation, 56, 540-562. https://doi.org/10.1108/ EUM0000000007127

  • Vakkari, P. and Huuskonen, S. (2012). Search effort degrades search output but improves task outcome. Journal of the American Society for Information Science and Technology, 63(4), 657-670. https://doi.org/10.1002/asi.21683

  • Vakkari, P., Jones, S., MacFarlane, A., and Sormunen, E. (2004). Query exhaustivity, relevance feedback and search success in automatic and interactive query expansion. Journal of Documentation, 60(2), 109-127. https://doi.org/10.1108/00220410410522016

  • Vakkari, P. and Kuokkanen, M. (1997).Theory growth in information science: Applications of the theory of science to a theory of information seeking. Journal of Documentation, 53(5), 497-519. https://doi.org/10.1108/EUM0000000007210

  • Vakkari, P., Pennanen, M. and Serola, S. (2003). Changes of search terms and tactics while writing a research proposal. Information Processing and Management, 39(3), 445-463. https://doi.org/10.1016/S0306-4573(02)00031-6

  • Vakkari, P., Volske, M., Potthast, M., Hagen, M. and Stein, B. (2019). Modelling the usefulness of search results as measured by information use. Information Processing and Management, 56(3), 879-894. https://doi.org/10.1016/j.ipm.2019.02.001

  • Vakkari, P., Volske, M., Potthast, M., Hagen, M. and Stein, B. (2021). Predicting essay quality from search and writing behavior. JASIST, 72(7), 839-852. https://doi.org/10.1002/asi.24451

  • Walhout, J., Oomen, P., Halszka, J. and Brand-Gruwel, S. (2017). Effects of task complexity on online search behavior of adolescents. Journal of the Association for Information Science and Technology, 68(6), 1449-1461. https://doi.org/10.1002/asi.23782

  • Wang P. (1997). User’s information needs at different stages of a research project: A cognitive view. In: Vakkari P, Savolainen R and Dervin B. (eds.), Information Seeking in Context (pp. 307-318). London and Los Angeles: Taylor Graham.

  • Wang, P. and Soergel, D. (1998). A cognitive model of document use during a research project: Study I: Document selection. Journal of the American Society for Information Science and Technology, 49(2), 115-133. https://doi.org/10.1002/(SICI)1097-4571(199802)49:2<115::AID-ASI3>3.0.CO;2-T

  • Wang, P., and White, M. D. (1999). A cognitive model of document use during a research project. Study II. Decisions at the reading and citing stages. Journal of the American Society for Information Science, 50, 98-114. https:// doi.org/10.1002/(SICI)1097-4571(1999)50:2<98::AIDASI2>3.0.CO;2-L

  • Wildemuth, B. M., de Bliek, R., Friedman, C. P., and File, D. D. (1995). Medical students’ personal knowledge, searching proficiency, and database use in problem solving. J Am Soc Inf Sci Technol, 46(8), 590-607. https://doi. org/10.1002/(SICI)1097-4571(199509)46:8<590::AID-ASI7>3.0.CO;2-#

  • Zhang, P. and Soergel, D. (2014). Towards a comprehensive model of the cognitive process and mechanisms of individual sensemaking. Journal of the Association for Information Science and Technology, 65(9), 1733-1758. https://doi.org/10.1002/asi.23125

  • Zhang, P. and Soergel, D. (2016) Process patterns and conceptual changes in knowledge representations during information seeking and sensemaking: A qualitative user study. Journal of Information Science, 42(1), 59-78. https://doi.org/10.1177/0165551515615834

  • Zhang, X., Liu, J., Cole, M. and Belkin, N. (2015). Predicting users’ domain knowledge in information retrieval using multiple regression analysis of search behaviors. Journal of the Association for Information Science and Technology, 66(5), 980-1000. https://doi.org/10.1002/asi.23218


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  • Information Search Patterns in Complex Tasks

Abstract Views: 260  |  PDF Views: 3

Authors

Pertti Vakkari
Tampere University, FIN - 33014, Finland

Abstract


This paper seeks to analyze information search process in complex tasks1. Complex tasks are larger tasks, which lead people to engage in search tasks for finding information to advance those tasks. Search process consists of activities from query formulation to working with sources selected for task outcome. This paper approaches task performance from the cognitive point of view conceptualizing it as changes in knowledge structures. These structures consist of concepts and their relations representing some phenomenon. Changes in knowledge structures are associated to query formulation and search tactics, selecting contributing sources and working with sources for creating task outcome. As a result, hypotheses concerning associations between changes in knowledge structures and search behaviors are suggested. The paper also presents some ideas for success indicators at various stages of search processes.

Keywords


Cognitive Search, Information Seeking, Information Search Process, Information User, Search Outcome.

References





DOI: https://doi.org/10.17821/srels%2F2023%2Fv60i1%2F170892