Michael J. Cole
Nicholas J. Belkin
Chirag Shah
ABSTRACT
Can the activity patterns of page use during information search sessions discriminate between different types of information seeking tasks? We model sequences of interactions with search result and content pages during information search sessions. Two representations are created: the sequences of page use and a cognitive representation of page interactions. The cognitive representation is based on logged eye movement patterns of textual information acquisition via the reading process. Page sequence actions from task sessions (n=109) in a user study are analyzed. The study tasks differed from one another in basic dimensions of complexity, specificity,level, and the type of information product (intellectual or factual). The results show that differences in task types can be measured at both the level of observations of page type sequences and at the level of cognitive activity on the pages. We discuss the implications for personalization of search systems, measurement of task similarity and the development of user-centered information systems that can support the user's current and expected search intentions.
- Alonso, O., Gertz, M., and Baeza-Yates, R. A. On the value of temporal information in information retrieval. SIGIR Forum 41, 2 (2007), 35--41. Google Scholar
Digital Library
- Bierig, R., Gwizdka, J., and Cole, M. J. A user-centered experiment and logging framework for interactive information retrieval. In Proceedings of the SIGIR 2009 Workshop on Understanding the User: Logging and interpreting user interactions in information search and retrieval. (July 2009), N. J. Belkin, R. Bierig, G. Buscher, L. van Elst, J. Gwizdka, J. Jose, and J. Teevan, Eds., CEUR, p. 8--11.Google Scholar
- Borlund, P. The IIR evaluation model: A framework for evaluation of interactive information retrieval systems. Information Research 8, 3 (2003).Google Scholar
- Buscher, G., Dengel, A., and van Elst, L. Query expansion using gaze-based feedback on the subdocument level. In Proceedings of SIGIR '08 (Singapore, 2008), ACM, pp. 387--394. Google ScholarDigital Library
- Cole, M. J., Gwizdka, J., Liu, C., Belkin, N. J., Bierig, R., and Zhang, X. Task and user effects on reading patterns in information search. Interacting with Computers 23, 4 (July 2011), 346--362.Google ScholarCross Ref
- Cole, M. J., Gwizdka, J., Liu, C., and Belkin, N. J. Dynamic assessment of information acquisition effort during interactive search. In Proceedings of the American Society for Information Science and Technology Conference (2011) (New Orleans, LA, October 2011), vol. 48, ASIST, p. 1--10.Google ScholarCross Ref
- Cole, M. J., Gwizdka, J., Liu, C., Belkin, N. J.,Bierig, R., and Zhang, X. Inferring user knowledge level from eye movement patterns, Information Processing & Management 49 (November 2012), 1075--1091. Google ScholarDigital Library
- Findlay, J., and Gilchrist, I. Active Vision: ThePsychology of Looking and Seeing. Oxford University Press, New York, 2003.Google Scholar
- Gao, B., Liu, T.-Y., Liu, Y., Wang, T., Ma, Z.-M., and Li, H. Page importance computation based on Markov processes. Information Retrieval 14, 5 (Oct.2011), 488--514. Google ScholarDigital Library
- Gwidka, J. Cognitive load and web search tasks. HCIR, 2009. Washington D.C.Google Scholar
- Gwizdka, J. and Spence, I. What can searching behavior tell us about the difficulty of information tasks? A study of Web navigation. Proceedings of the American Society for Information Science and Technology 43, 1 (2006), 1--22.Google ScholarCross Ref
- Han, S., Yue, Z., and He, D. Automatic detection of search tactic in individual information seeking: A Hidden Markov Model Approach. In iConference 2013 Proceedings (2013), pp. 712--716.Google Scholar
- Hendahewa, C., and Shah, C. Segmental analysis and evaluation of user focused search process. In International Conference on Machine Learning and Applications (ICMLA) (2013), IEEE, pp. 291--294. Google ScholarDigital Library
- Inhoff, A. W., and Liu, W. The perceptual span and oculomotor activity during the reading of Chinese sentences. Journal of Experimental Psychology. Human Perception and Performance 24, 1 (1998), 20--34.Google ScholarCross Ref
- Kellar, M., Watters, C., and Shepherd, M. A field study characterizing Web-based information-seeking tasks. JASIST 58, 7 (2007), 999--1018. Google ScholarDigital Library
- Li, Y. Relationships among work tasks, search tasks,and interactive information searching behavior. PhD thesis, Rutgers University, 2008.Google Scholar
- Li, Y. Exploring the relationships between work task and search task in information search. JASIST, pp. 275--291, 2009. Google ScholarDigital Library
- Liu, Y., Ma, Z.-M., and Zhou, C. Web Markov skeleton processes and their applications. Tohoku Mathematical Journal 63, 4 (2011), 665--695.Google ScholarCross Ref
- Marchionini, G. Information-seeking strategies of novices using a full-text electronic encyclopedia. JASIST 40, 1 (1989), 54--66. Google ScholarDigital Library
- Marchionini, G., and Maurer, H. The roles of digital libraries in teaching and learning.Communications of the ACM 38, 4 (1995), 67--75. Google ScholarDigital Library
- Morris, R. Lexical and message-level sentence context effects on fixation times in reading. Journal of Experimental Psychology: Learning, Memory, and Cognition 20, 1 (1994), 92.Google Scholar
- Pollatsek, A., Rayner, K., and Balota, D. A. Inferences about eye movement control from the perceptual span in reading. Perception & Psychophysics 40, 2 (1986), 123--130.Google ScholarCross Ref
- Qiu, L. Markov models of search state patterns in a hypertext information retrieval system. JASIST 44, 7 (1993), 413--427. Google ScholarDigital Library
- Rayner, K. Eye movements in reading and information processing: 20 years of research. Psychological Bulletin 124 (1998), 372--422.Google ScholarCross Ref
- Rayner, K., Chace, K. H., Slattery, T. J., and Ashby, J. Eye movements as reflections of comprehension processes in reading. Scientific Studiesof Reading 10, 3 (2006), 241--255.Google ScholarCross Ref
- Rayner, K., and Pollatsek, A. The Psychology of Reading. Lawrence Erlbaum Associates, Mahwah, New Jersey, 1989.Google Scholar
- Reichle, E. D., Pollatsek, A., and Rayner, K. EZ Reader: A cognitive-control, serial-attention model of eye-movement behavior during reading. Cognitive Systems Research 7, 1 (2006), 4--22. Google ScholarDigital Library
- Reichle, E. D., Rayner, K., and Pollatsek, A. The EZ Reader model of eye-movement control in reading: Comparisons to other models. Behavioral and Brain Sciences 26, 04 (2004), 445--476.Google Scholar
- Reingold, E., and Rayner, K. Examining the word identification stages hypothesized by the EZ Reader model. Psychological Science 17, 9 (2006), 742--746.Google ScholarCross Ref
- Sereno, S. C., O'Donnell, P., and Rayner, K. Eye movements and lexical ambiguity resolution: Investigating the subordinate-bias effect. Journal of Experimental Psychology: Human Perception and Performance 32, 2 (2006), 335.Google ScholarCross Ref
- Triesch, J., Ballard, D. H., Hayhoe, M. M., and Sullivan, B. T. What you see is what you need. Journal of Vision 3 (2003), 86--94.Google ScholarCross Ref
- Tsai, C., and McConkie, G. The perceptual span in reading Chinese text: A moving window study. In Seventh International Conference on the Cognitive Processing of Chinese and Other Asian Languages, Hong Kong (1995).Google Scholar
- White, R. W., and Kelly, D. A study on the effects of personalization and task information on implicit feedback performance. In CKIM'06 (Arlington, Virginia,USA, November 2006), ACM, pp. 297--306. Google ScholarDigital Library
- Williams, R., and Morris, R. Eye movements, word familiarity, and vocabulary acquisition. Journal of Cognitive Psychology 16, 1 (2004), 312--339.Google Scholar
Index Terms
- Discrimination between tasks with user activity patterns during information search
Recommendations
User Activity Patterns During Information Search
Special Issue on Contextual Search and RecommendationPersonalization of support for information seeking depends crucially on the information retrieval system's knowledge of the task that led the person to engage in information seeking. Users work during information search sessions to satisfy their task ...
Linking search tasks with low-level eye movement patterns
ECCE '10: Proceedings of the 28th Annual European Conference on Cognitive ErgonomicsMotivation -- On-the-task detection of the task type and task attributes can benefit personalization and adaptation of information systems.
Research approach -- A web-based information search experiment was conducted with 32 participants using a multi-...
Inferring user knowledge level from eye movement patterns
The acquisition of information and the search interaction process is influenced strongly by a person's use of their knowledge of the domain and the task. In this paper we show that a user's level of domain knowledge can be inferred from their ...
Comments