Predicting Search Performance from Mobile Touch Interactions on Cross-device Search Engine Result Pages

1. Dearman, D., Pierce, S.: It’s on my other computer!: computing with multiple devices. In: SIGCHI Conference on Human Factors in Computing Systems, pp. 767–776. ACM, New York (2008)

   Google Scholar 

2. Vetro Analytics. http://www.vertoanalytics.com/verto-reports/. Accessed 11 Sept 2017

3. Montañez, D., White, W., Huang X.: Cross-device search. In: 23rd ACM International Conference on Information and Knowledge Management, pp. 1669–1678. ACM, New York (2014)

   Google Scholar 

4. Guo, Q., Jin, H., Lagun, D., et al.: Towards estimating web search result relevance from touch interactions on mobile devices. In: CHI 2013 Extended Abstracts on Human Factors in Computing Systems, pp. 1821–1826. ACM. New York (2013)

   Google Scholar 

5. Fox, S., Karnawat, K., Mydland, M., et al.: Evaluating implicit measures to improve web search. ACM Trans. Inf. Syst. 23(2), 147–168 (2005)

   Article  Google Scholar 

6. Huang, J., White, W., Dumais, S.: No clicks, no problem: using cursor movements to understand and improve search. In: SIGCHI Conference on Human Factors in Computing Systems, pp. 1225–1234. ACM, New York (2011)

   Google Scholar 

7. Han, S., Hsiao, I.-H., Parra, D.: A study of mobile information exploration with multi-touch interactions. In: Kennedy, W.G., Agarwal, N., Yang, S.J. (eds.) SBP 2014. LNCS, vol. 8393, pp. 269–276. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-05579-4_33

   Chapter  Google Scholar 

8. Biedert, R., Dengel, A., Buscher, G., et al.: Reading and estimating gaze on smart phones. In: Proceedings of Symposium on Eye Tracking Research and Applications, pp. 385–388. ACM, New York (2012)

   Google Scholar 

9. Tran, J., Trewin, S., Swart, C., et al.: Exploring pinch and spread gestures on mobile devices. In: 15th International Conference on Human-Computer Interaction with Mobile Devices and Services, pp. 151–160. ACM, New York (2013)

   Google Scholar 

10. Kim, J., Thomas, P., Sankaranarayana, R., et al.: What snippet size is needed in mobile web search? In: 2017 Conference on Conference Human Information Interaction and Retrieval, pp. 97–106. ACM, New York (2017)

    Google Scholar 

11. Hotchkiss, G., Alston, S., Edwards, G.: Eye tracking study. Research White paper, Enquiro Search Solutions, Kelowna, Canada (2005)

    Google Scholar 

12. Guo, Q., Jin, H., Lagun, D., et al.: Mining touch interaction data on mobile devices to predict web search result relevance. In: 36th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 153–162. ACM, New York (2013)

    Google Scholar 

13. Han, S., Yue, Z., He, D.: Understanding and supporting cross-device web search for exploratory tasks with mobile touch interactions. ACM Trans. Inf. Syst. 33(4), 1–34 (2015)

    Article  Google Scholar 

14. Kim, Y., Hassan, A., White, W., et al.: Playing by the rules: mining query associations to predict search performance. In: 6th ACM International Conference on Web Search and Data Mining, pp. 133–142. ACM, New York (2013)

    Google Scholar 

15. Ahn, W., Brusilovsky, P., He, D., et al.: Personalized web exploration with task models. In: 17th International Conference on World Wide Web, pp. 1–10. ACM, New York (2008)

    Google Scholar 

16. Li, Y., Xu, P., Lagun, D., et al.: Towards measuring and inferring user interest from gaze. In: 26th International Conference on World Wide Web Companion, pp. 525–533. ACM, New York (2017)

    Google Scholar 

17. Wang, Y., Huang, X., White, W.: Characterizing and supporting cross-device search tasks. In: 6th ACM International Conference on Web Search and Data Mining, pp. 707–716. ACM, New York (2013)

    Google Scholar 

18. Kotov, A., Bennett, N., White, W., et al.: Modeling and analysis of cross-session search tasks. In: 34th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 5–14. ACM, New York (2011)

    Google Scholar 

19. Kelly, D., Belkin, N.J.: Reading time, scrolling and interaction: exploring implicit sources of user preferences for relevance feedback. In: 24th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 408–409. ACM, New York (2001)

    Google Scholar 

20. Kim, J., Thomas, P., Sankaranarayana, R., et al.: Pagination versus scrolling in mobile web search. In: 25th ACM International on Conference on Information and Knowledge Management, pp. 751–760. ACM, New York (2016)

    Google Scholar 

21. Guo, Q., Yuan, S., Agichtein, E.: Detecting success in mobile search from interaction. In: 34th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 1220–1230. ACM, New York (2011)

    Google Scholar 

22. Avery, J., Choi, M., Vogel, D., et al.: Pinch-to-zoom-plus: an enhanced pinch-to-zoom that reduces clutching and panning. In: 27th Annual ACM Symposium on User Interface Software and Technology, pp. 595–604. ACM, New York (2014)

    Google Scholar 

23. Wu, D., Yao, X., Dong, J., et al.: Designing mobile search tasks: a context-based approach. Geomat. Inf. Sci. Wuhan Univ. 41, 34–39 (2017)

    Google Scholar 

24. Zhan, K., Zukerman, I., Moshtaghi, M., et al.: Eliciting users’ attitudes toward smart devices. In: 2016 Conference on User Modeling Adaptation and Personalization, pp. 175–184. ACM, New York (2016)

    Google Scholar 

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