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 ( hearst@ischool.berkeley.edu) 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.