68 BIBLIOGRAPHY
2015 International Conference on the eory of Information Retrieval (pp. 101–110). ACM.
DOI: 10.1145/2808194.2809465. 30
Kelly, D. and Azzopardi, L. (2015). How many results per page? A study of serp size, search be-
havior and user experience. In Proceedings of the 38th International ACM SIGIR Confer-
ence on Research and Development in Information Retrieval (pp. 183–192). ACM. DOI:
10.1145/2766462.2767732. 21, 43, 46
Kelly, D. and Fu, X. (2006). Elicitation of term relevance feedback: An investigation of term
source and context. In Proceedings of the 29th Annual International ACM SIGIR Confer-
ence on Research and Development in Information Retrieval (pp. 453–460). ACM. DOI:
10.1145/1148170.1148249. 12
Kelly, D. and Sugimoto, C. R. (2013). A systematic review of interactive information retrieval
evaluation studies, 1967–2006. Journal of the American Society for Information Science and
Technology, 64(4), 745–770. DOI: 10.1002/asi.22799. 8, 9, 18, 42, 53, 54
Kim, J., McNally, B., Norooz, L., and Druin, A. (2017). Internet search roles of adults in their
homes. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems
(pp. 4948–4959). ACM. DOI: 10.1145/3025453.3025572. 19
Kittur, A., Chi, E. H., and Suh, B. (2008). Crowdsourcing user studies with Mechanical Turk.
In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp.
453–456). ACM. DOI: 10.1145/1357054.1357127. 29
Klouche, K., Ruotsalo, T., Cabral, D., Andolina, S., Bellucci, A., and Jacucci, G. (2015). Design-
ing for exploratory search on touch devices. In Proceedings of the 33rd Annual ACM
Conference on Human Factors in Computing Systems (pp. 4189–4198). ACM. DOI:
10.1145/2702123.2702489. 43
Lagun, D. and Agichtein, E. (2015). Inferring searcher attention by jointly modeling user inter-
actions and content salience. In Proceedings of the 38th International ACM SIGIR Con-
ference on Research and Development in Information Retrieval (pp. 483–492). ACM. DOI:
10.1145/2766462.2767745. 18
Lagun, D., Hsieh, C. H., Webster, D., and Navalpakkam, V. (2014). Towards better measurement of
attention and satisfaction in mobile search. In Proceedings of the 37th International ACM
SIGIR Conference on Research and Development in Information Retrieval (pp. 113–122).
ACM. DOI: 10.1145/2600428.2609631. 8, 47
Law, E., Yin, M., Goh, J., Chen, K., Terry, M. A., and Gajos, K. Z. (2016). Curiosity killed the cat,
but makes crowdwork better. In Proceedings of the 2016 CHI Conference on Human Factors
in Computing Systems (pp. 4098–4110). ACM. DOI: 10.1145/2858036.2858144. 29
69BIBLIOGRAPHY
Li, Y. (2009). Exploring the relationships between work task and search task in information search.
Journal of the American Society for information Science and Technology, 60(2), 275–291.
DOI: 10.1002/asi.20977. 30
Li, Y. and Belkin, N. J. (2010). An exploration of the relationships between work task and interac-
tive information search behavior. Journal of the American Society for Information Science and
Technology, 61(9), 1771-1789. DOI: 10.1002/asi.21359. 30
Li, Y. and Belkin, N. J. (2008). A faceted approach to conceptualizing tasks in information
seeking. Information Processing and Management, 44(6), 1822–1837. DOI: 10.1016/j.
ipm.2008.07.005. 15, 23, 30
Li, Y., Dong, A., Wang, H., Deng, H., Chang, Y., and Zhai, C. (2014). A two-dimensional click
model for query auto-completion. In Proceedings of the 37th International ACM SIGIR
Conference on Research and Development in Information Retrieval (pp. 455–464). ACM.
DOI: 10.1145/2600428.2609571. 52
Liu, C., Belkin, N. J., and Cole, M. J. (2012). Personalization of search results using interaction
behaviors in search sessions. In Proceedings of the 35th International ACM SIGIR Confer-
ence on Research and Development in Information Retrieval (pp. 205–214). ACM. DOI:
10.1145/2348283.2348314. 7
Liu, J. (2017). Toward a unied model of human information behavior: an equilibrium perspective.
Journal of Documentation, 73(4), 666–688. DOI: 10.1108/JD-06-2016-0080. 39, 52, 53
Liu, J. (2019). A reference-dependent model of search evaluation. In Proceedings of the 2019 In-
ternational ACM SIGIR Conference on Human Information Interaction and Retrieval (pp.
405–408). ACM. DOI: 10.1145/3295750.3298970. 52, 53
Liu, J., Cole, M. J., Liu, C., Bierig, R., Gwizdka, J., Belkin, N. J., Zhang, J. and Zhang, X. (2010).
Search behaviors in dierent task types. In Proceedings of the 10th Annual Joint Conference
on Digital Libraries (pp. 69–78). ACM. DOI: 10.1145/1816123.1816134. 21, 27, 30
Liu, M., Liu, Y., Mao, J., Luo, C., Zhang, M., and Ma, S. (2018). “Satisfaction with failure” or” un-
satised success”: Investigating the relationship between search success and user satisfac-
tion. In Proceedings of the 2018 World Wide Web Conference (WWW’18) (pp. 1533–1542).
DOI: 10.1145/3178876.3186065. 26
Liu, J., Mitsui, M., Belkin, N. J., and Shah, C. (2019). Task, information seeking intentions, and user
behavior: Toward a multi-level understanding of Web search. In Proceedings of the 2019
Conference on Human Information Interaction and Retrieval (pp. 123–132). ACM. DOI:
10.1145/3295750.3298922. 7, 21, 42
70 BIBLIOGRAPHY
Liu, Y. H. and Wacholder, N. (2017). Evaluating the impact of MeSH (Medical Subject Headings)
terms on dierent types of searchers. Information Processing and Management, 53(4),
851–870. DOI: 10.1016/j.ipm.2017.03.004. 20
Luo, C., Liu, Y., Sakai, T., Zhang, F., Zhang, M., and Ma, S. (2017). Evaluating mobile search
with height-biased gain. In Proceedings of the 40th International ACM SIGIR Confer-
ence on Research and Development in Information Retrieval (pp. 435–444). ACM. DOI:
10.1145/3077136.3080795. 48, 49
Luo, J., Zhang, S., and Yang, H. (2014). Win-win search: Dual-agent stochastic game in session search.
In Proceedings of the 37th International ACM SIGIR Conference on Research and Develop-
ment in Information Retrieval (pp. 587–596). ACM. DOI: 10.1145/2600428.2609629. 3
Mao, J., Liu, Y., Kando, N., Zhang, M., and Ma, S. (2018). How does domain expertise aect users’
search interaction and outcome in exploratory search? ACM Transactions on Information
Systems (TOIS), 36(4), 42. DOI: 10.1145/3223045. 20
Mao, J., Liu, Y., Zhou, K., Nie, J. Y., Song, J., Zhang, M., Ma, S., Sun, J. and Luo, H. (2016). When
does relevance mean usefulness and user satisfaction in web search? In Proceedings of the
39th International ACM SIGIR Conference on Research and Development in Information
Retrieval (pp. 463–472). ACM. DOI: 10.1145/2911451.2911507. 13, 49
Mitsui, M., Liu, J., Belkin, N. J., and Shah, C. (2017). Predicting information seeking intentions
from search behaviors. In Proceedings of the 40th International ACM SIGIR Conference
on Research and Development in Information Retrieval (pp. 1121–1124). ACM. DOI:
10.1145/3077136.3080737. 30
Moat, A., Bailey, P., Scholer, F., and omas, P. (2017). Incorporating user expectations and be-
havior into the measurement of search eectiveness. ACM Transactions on Information
Systems (TOIS), 35(3), 24. DOI: 10.1145/3052768. 12
Morris, M. R., Fourney, A., Ali, A., and Vonessen, L. (2018). Understanding the needs of searchers
with dyslexia. In Proceedings of the 2018 CHI Conference on Human Factors in Computing
Systems (p. 35). ACM. DOI: 10.1145/3173574.3173609. 19
Moshfeghi, Y. and Jose, J. M. (2013). An eective implicit relevance feedback technique using aec-
tive, physiological and behavioural features. In Proceedings of the 36th International ACM
SIGIR Conference on Research and Development in Information Retrieval (pp. 133–142).
ACM. DOI: 10.1145/2484028.2484074. 48
Moshfeghi, Y., Triantallou, P., and Pollick, F. E. (2016). Understanding information need:
An fMRI study. In Proceedings of the 39th International ACM SIGIR Conference
71BIBLIOGRAPHY
on Research and Development in Information Retrieval (pp. 335–344). ACM. DOI:
10.1145/2911451.2911534. 2, 8, 28, 34, 59
Nicholson, J., Huber, M., Jackson, D., and Olivier, P. (2014). Panopticon as an eLearning support
search tool. In Proceedings of the SIGCHI Conference on Human Factors in Computing Sys-
tems (pp. 1221–1224). ACM. DOI: 10.1145/2556288.2557082. 31
O’Brien, H. L. and McCay-Peet, L. (2017). Asking good questions: Questionnaire design and
analysis in interactive information retrieval research. In Proceedings of the 2017 Conference
on Conference Human Information Interaction and Retrieval (pp. 27–36). ACM. DOI:
10.1145/3020165.3020167. 3
Ong, K., Järvelin, K., Sanderson, M., and Scholer, F. (2017). Using information scent to understand
mobile and desktop web search behavior. In Proceedings of the 40th International ACM
SIGIR Conference on Research and Development in Information Retrieval (pp. 295–304).
ACM. DOI: 10.1145/3077136.3080817. 7, 11, 19, 26, 32, 43
Robertson, S. (2008). On the history of evaluation in IR. Journal of Information Science, 34(4),
439–456. DOI: 10.1177/0165551507086989. xvi, 3, 5, 58
Ruotsalo, T., Peltonen, J., Eugster, M. J., Głowacka, D., Floréen, P., Myllymäki, P., Jacucci, G., and
Kaski, S. (2018). Interactive intent modeling for exploratory search. ACM Transactions on
Information Systems (TOIS), 36(4), 44. DOI: 10.1145/3231593. 26, 31, 43
Ruthven, I. (2008). Interactive information retrieval. Annual Review of Information Science and Tech-
nology, 42(1), 43–91. DOI: 10.1002/aris.2008.1440420109. 7, 13
Sakai, T. (2016). Statistical signicance, power, and sample sizes: A systematic review of SIGIR
and TOIS, 2006-2015. In Proceedings of the 39th International ACM SIGIR Confer-
ence on Research and Development in Information Retrieval (pp. 5–14). ACM. DOI:
10.1145/2911451.2911492. 9, 29, 37, 42, 53, 54, 57
Sanderson, M. and Zobel, J. (2005). Information retrieval system evaluation: Eort, sensitivity,
and reliability. In Proceedings of the 28th Annual International ACM SIGIR Conference
on Research and Development in Information Retrieval (pp. 162–169). ACM. DOI:
10.1145/1076034.1076064. 9
Saracevic, T. (1975). Relevance: A review of and a framework for the thinking on the notion in
information science. Journal of the American Society for Information Science, 26(6), 321–343.
DOI: 10.1002/asi.4630260604. 47
Shah, C. (2018). Information fostering-Being proactive with information seeking and retrieval:
Perspective paper. In Proceedings of the 2018 Conference on Human Information Interaction
and Retrieval (pp. 62–71). ACM. DOI: 10.1145/3176349.3176389. 7
72 BIBLIOGRAPHY
Shah, C. and Marchionini, G. (2010). Awareness in collaborative information seeking. Journal of
the American Society for Information Science and Technology, 61(10), 1970–1986. DOI:
10.1002/asi.21379. 12
Shah, C., Pickens, J., and Golovchinsky, G. (2010). Role-based results redistribution for collabora-
tive information retrieval. Information Processing and Management, 46(6), 773–781. DOI:
10.1016/j.ipm.2009.10.002.43
Singla, A., White, R., and Huang, J. (2010). Studying trailnding algorithms for enhanced web search.
In Proceedings of the 33rd International ACM SIGIR Conference on Research and Develop-
ment in Information Retrieval (pp. 443–450). ACM. DOI: 10.1145/1835449.1835524. 18
Smith, C. L., Gwizdka, J., and Feild, H. (2017). e use of query auto-completion over the course
of search sessions with multifaceted information needs. Information Processing and Man-
agement, 53(5), 1139–1155. DOI: 10.1016/j.ipm.2017.05.001. 20
Smucker, M. D. and Jethani, C. P. (2010). Human performance and retrieval precision revisited. In
Proceedings of the 33rd International ACM SIGIR Conference on Research and Development
in Information Retrieval (pp. 595–602). ACM. DOI: 10.1145/1835449.1835549. 48
Song, Y., Ma, H., Wang, H., and Wang, K. (2013). Exploring and exploiting user search be-
havior on mobile and tablet devices to improve search relevance. In Proceedings of
the 22nd International Conference on World Wide Web (pp. 1201–1212). ACM. DOI:
10.1145/2488388.2488493. 32
Spink, A., Yang, Y., Jansen, J., Nykanen, P., Lorence, D. P., Ozmutlu, S., and Ozmutlu, H. C. (2004).
A study of medical and health queries to web search engines. Health Information and
Libraries Journal, 21(1), 44–51. DOI: 10.1111/j.1471-1842.2004.00481.x. 3
Sun, S. and Belkin, N. J. (2015). Information attribute motivators of personal health information
management activities. In Proceedings of the 78th ASIS&T Annual Meeting (pp. 1–9).
DOI: 10.1002/pra2.2015.145052010046. 21
Suominen, H., Kelly, L., Goeuriot, L., Névéol, A., Ramadier, L., Robert, A., Kanoulas, E., Spijker,
R., Azzopardi, L., Li, D., Palotti, J., and Zuccon, G. (2018). Overview of the CLEF
eHealth evaluation lab 2018. In International Conference of the Cross-Language Evaluation
Forum for European Languages (pp. 286–301). Springer, Cham. DOI: 10.1007/978-3-
319-98932-7_26. 55
Syed, R. and Collins-ompson, K. (2017). Retrieval algorithms optimized for human learning. In
Proceedings of the 40th International ACM SIGIR Conference on Research and Development
in Information Retrieval (pp. 555–564). ACM. DOI: 10.1145/3077136.3080835. 12, 31,
46, 47
..................Content has been hidden....................
You can't read the all page of ebook, please click here login for view all page.