books is still not particularly sophisticated, search over movie-length videos may well prove problematic and require alternative approaches.

conclusion

The future of user interfaces will involve support for natural human interaction, gesturing with fingers, speaking rather than typing, watching video rather than reading, and using IT socially rather than alone. This article has explored why these trends will also affect user interfaces for search, highlighting recent work reflecting these trends. Using advanced processing techniques over huge sets of behavioral data, future search interfaces will better support finding other people to answer questions or provide opinions, more natural dialogue-like interaction, and information expressed as non-textual content through non-textual input. More-natural modes of interaction have long been goals of interface design, but recent developments have brought them closer to reality.

 

References

1. adamic, l.a., Zhang, J., bakshy, e., and ackerman, m.s. Knowledge sharing and yahoo answers: everyone knows something. In Proceedings of the 17th International Conference on the World Wide Web (beijing). aCm Press, new york, 2008, 665–674.

2. bian, J., liu, y., agichtein, e., and Zha, h. Finding the right facts in the crowd: Factoid question answering over social media. In Proceedings of the 17th International Conference on the World Wide Web (beijing). aCm Press, new york, 2008, 467–476.

3. bilal, d. Children’s use of the yahooligans! web search engine: I. Cognitive, physical, and affective behaviors on fact-based search tasks. Journal of the American Society of Information Science 51, 7 (2000), 646–65.

4. Chaudhri, V.K., Cheyer, a., guili, r., Jarrold, b., myers, K.l., and niekrasz, J. a case study in engineering a knowledge base for an intelligent personal assistant. In Proceedings of the 2006 Semantic Desktop Workshop (athens, ga, 2006).

5. Church, K., neumann, J., Cherubini, m., and oliver, n. the map trap: an evaluation of map versus text-based interfaces for location-based mobile search services. In Proceedings of the 19th International Conference on the World Wide Web (raleigh, nC, apr. 26–30). aCm Press, new york, 2010, 261–270.

6. comscore. comscore releases march 2010 u.s. search engine rankings (mar. 2010); http://www.comscore.com/Press_events/ Press_releases/2010/4/comscore_releases_ march_2010_u.s._search_engine_rankings

7. diaz, F. and arguello, J. adaptation of offline vertical selection predictions in the presence of user feedback. In Proceedings of the 32nd International ACM SIGIR Conference on Research and Development on Information Retrieval (boston, July 19–23). aCm Press, new york, 323–330.

8. erlewine, m.y. ubiquity: designing a multilingual natural language interface. In Proceedings of the SIGIR Workshop on Information Access in a Multilingual World (boston, July 19–23). aCm Press, new york, 2009.

9. Ferrucci, d., brown, e, Chu-Carroll, J., Fan, J., gondek, d., Kalyanpur, a.a., lally, a., murdock, J.w., nyberg, e., Prager, J., et al. building watson: an overview of the deepQa Project. AI Magazine 31, 3 (2010).

10. Freyne, J., Farzan, r., brusilovsky, P., smyth, b., and Coyle, m. Collecting community wisdom: Integrating social search & social navigation. In Proceedings of the 12th International Conference on Intelligent User Interfaces (honolulu, Jan. 28–31). aCm Press, new york, 2007, 52–61.

11. golovchinsky, g., shah, C., and Pickens, J. role-based results redistribution for collaborative information retrieval. Information Processing and Management 46, 6 (2010), 773–781.

12. harper, F.m., moy, d., and Konstan, J.a. Facts or friends?: distinguishing informational and conversational questions in social Q&a sites. In Proceedings of the 27th International Conference on Human Factors in Computing Systems (boston, apr. 4–9). aCm Press, new york, 2009, 759–768.

13. hearst, m. Search User Interfaces. Cambridge university Press, 2009.

14. hitwise. Facebook was the top search term in 2010 for second straight year (dec. 29 2010); http:// www.hitwise.com/us/press-center/press-releases/ facebook-was-the-top-search-term-in-2010-for-sec/

15. horowitz, d. and Kamvar, s.d. the anatomy of a large-scale social search engine. In Proceedings of the 19th International Conference on the World Wide Web (raleigh, nC, apr. 26–30). aCm Press, new york, 431–440.

16. Jetter, h.-C., gerken, J., Zöllner, m., reiterer, h., and milic-Frayling, n. materializing the query with facet-streams: a hybrid surface for collaborative search on tabletops. In Proceedings of the 29th International Conference on Human Factors in Computing Systems (Vancouver, Canada, may 7–12). aCm Press, new york, 2011.

17. Joachims, t., granka, l., Pan, b., hembrooke, h., and gay, g. accurately interpreting clickthrough data as implicit feedback. In Proceedings of the 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (salvador, brazil, aug. 15–19). aCm Press, new york, 2005, 154–161.

18. Kautz, h., selman, b., and shah, m. referral web: Combining social networks and collaborative filtering. Commun. ACM 40, 3 (mar. 1997), 63–65.

19. li, y. gesture search: a tool for fast mobile data access. In Proceedings of the 23rd Annual ACM Symposium on User Interface Software and Technology (new york, oct. 3–6). aCm Press, new york, 87–96.

20. liu, C., rau, P.l.P., and gao, F. mobile information search for location-based information. Computers in Industry 61, 4 (may 2010), 364–371.

21. liu, y. and agichtein, e. you’ve got answers: towards personalized models for predicting success in community question answering. In Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies (Columbus, oh, June 15–20). association for Computational linguistics, stroudsburg, Pa, 2008, 97–100.

22. mcgee, m. the long tail is alive and well. Small Business Search Marketing (sept. 16, 2010); http:// www.smallbusinesssem.com/long-tail-alive- well/3659/ and http://twitter.com/hitwise_us/ status/24041444164

23. miller, r.C., Chou, V.h., bernstein, m., little, g., Van Kleek, m., and Karger, d. Inky: a sloppy command line for the web with rich visual feedback. In Proceedings of the 21st annual ACM Symposium on User Interface Software and Technology (monterey, Ca, oct. 19–22). aCm Press, new york, 2008, 131–140.

24. morris, m.r., teevan, J., and Panovich, K. what do people ask their social networks, and why?: a survey study of status message Q&a behavior. In Proceedings of the 28th International Conference on Human Factors in Computing Systems (atlanta, apr. 10–15). aCm Press, new york, 2010, 1739–1748.

25. norman, d. the next uI breakthrough: Command lines. Interactions 14, 3 (2007), 44–45.

26. noveck, b.s. Peer to patent: Collective intelligence, open review, and patent reform. Harvard Journal of Law & Technology 20, 1 (2006), 123–162.

27. over, P., awad, g., Fiscus, J., antonishek, b., and michel, m. treCVId 2010: an introduction to the goals, tasks, data, evaluation mechanisms, and metrics. Proceedings of the Eighth TRECVID Workshop. national Institute of standards and technology, gaithersburg, md, 2010.

28. Peres, J.C. google wants your phonemes. Info World
(oct. 23, 2007); http://www.infoworld.com/t/data-
management/google-wants-your-phonemes-539

 

Marti A. hearst ( [e-mail]) is a professor in the school of Information at the university of California, berkeley, with an affiliate position in the Computer science division. she is the author of Search User Interfaces, Cambridge university Press, 2009.