Mobile Search文献调研

Published: 18 Mar 2011 Category:



2.Mobile search features(移动搜索特点研究)

3.Hot topics(热点研究方向)

4.Research Resources(研究资源:有关会议、组织等)


  1. [1] F. Tsai, M. Etoh, X. Xie, and W. Lee, "Introduction to mobile information retrieval," IEEE Intelligent Systems, 2010, pp. 11-15.
  2. K. Church, B. Smyth, and P. Cotter, "Mobile information access: A study of emerging search behavior on the mobile Internet," ACM Transactions on the, vol. 1, May. 2007, p. 4-es.
  3. Roto, V. (2006), Search on mobile phones. Journal of the American Society for Information Science and Technology, 57: 834–837. doi: 10.1002/asi.203
  4. S.G. Nikolov, R. Compañó, M. Bacigalupo, and C. Feijóo, "What is Missing for the Full Deployment of Mobile Search Services ? Results from a Survey with Experts," Technology, 2010, pp. 1-9.
  5. "Introduction to Mobile Search,"Technical report,Mobile Marketing Association。January 2006
  6. Mobile Search Tutorial
  7. M. Jones, Mobile Search Tutorial, 2009.
Mobile search features
  1. T. Sohn, K. a Li, W.G. Griswold, and J.D. Hollan, "A diary study of mobile information needs," Proceeding of the twenty-sixth annual CHI conference on Human factors in computing systems - CHI '08, 2008, p. 433.
  2. Kamvar, M., Baluja, S. A Large Scale Study of Wireless Search Behavior: Google Mobile Search. In Proc. of CHI 2006, pp. 701-709.
  3. J. Yi, F. Maghoul, and J. Pedersen, "Deciphering Mobile Search Patterns : A Study of Yahoo ! Mobile Search Queries," Distribution, 2010, pp. 257-266.
  4. K. Church, B. Smyth, K. Bradley, and P. Cotter, "A large scale study of European mobile search behaviour," Proceedings of the 10th international conference on Human computer interaction with mobile devices and services - MobileHCI '08, 2008, p. 13.
  5. Lee, I. et al. Use Contexts for the Mobile Internet: A Lon- gitudinal Study Monitoring Actual Use of Mobile Internet Services. Journal of Human-Computer Interaction, 18(3), pp. 269-292.
  6. M. Kamvar, M. Kellar, R. Patel, and Y. Xu, "Computers and iphones and mobile phones, oh my!," Proceedings of the 18th international conference on World wide web - WWW '09, 2009, p. 801.
Hot topics:

Two main themes characterize research in this growing area: context awareness and content adaptation[1].


context awareness:

Mobile devices have more features than their computer counterparts, including location information, built- in cameras, and certain social networks.

  1. F.S. Tsai et al., "Design and Development of a Mobile Peer-to-Peer Social Networking Application," Expert Systems with Applications, vol. 36, no. 8, 2009, pp. 11077–11087.
  2. S. Mizzaro and E. Nazzi, "Retrieval of context-aware applications on mobile devices: how to evaluate?," Proceedings of the second, 2008, pp. 65-71.
  3. Mobile search can also be enhanced with images, audio, video, and their combinations for a richer experience.
  4. X. Xie et al., "Mobile Search with Multimodal Queries," Proc. IEEE, vol. 96, no. 4, 2008, pp. 589–601.
  5. X. Fan, X. Xie, Z. Li, M. Li, and W.-ying Ma, "Photo-to-Search : Using Multimodal Queries to Search the Web from Mobile Devices," Science And Technology, 2005, pp. 143-150.
    Location-based search
  6. T. Tezuka, T. Kurashima, and K. Tanaka, "Toward Tighter Integra- tion of Web Search with a Geographic Information System," Proc. 15th Int'l Conf. World Wide Web (WWW 06),
  7. D. Choi, "Personalized local internet in the location-based mobile web search," Decision Support Systems, vol. 43, Feb. 2007, pp. 31-45.
  8. M. Jones, G. Buchanan, R. Harper, P.-louis Xech, J.J.T. Ave, and C. Uk, "Questions Not Answers : A Novel Mobile Search Technique," Science, 2007, pp. 155-158.
    Extraction of useful semantics
  9. K.Y. Yee et al., "OntoMobiLe: A Generic Ontology-Centric Service-Oriented Architecture for Mobile Learning," Proc. 10th Int'l Conf. Mobile Data Management: Systems, Services and Middleware (MDM 09), IEEE CS Press, 2009, pp. 631–636.
  10. Data mining of query logs, clicks, and Web traffic on mobile devices
  11. A.T. Kwee and F.S. Tsai, "Mobile Novelty Mining," Int'l J. Advanced Pervasive and Ubiquitous Computing, to be published, 2010.
Content Adaptation
  • Small screens and low-power and low-memory devices.

  • Many of these areas can adapt existing IR technologies for mobile data, such as content-based extraction, indexing, annotation, and retrieval of mobile data
  • power and efficiency distinguish the really useful algorithms
    Content adaptation for smalldisplay devices includes automatic summarization and personalization in mobile information
  1. K. Church and B. Smyth, "Who , What , Where & When : A New Approach to Mobile Search," 2008, pp. 309-312.interface technologies(interaction)

  2. A. Karlson, G. Robertson, and D. Robbins, "FaThumb: a facet-based interface for mobile search," Proceedings of the, 2006, pp. 711-720.

  3. Kamvar, M. and Baluja, S. 2008. Query suggestions for mobile search: understanding usage patterns. In Proceeding of the Twenty-Sixth Annual SIGCHI Conference on Human Factors in Computing Systems (Florence, Italy, April 05 - 10, 2008). CHI '08. ACM, New York, NY, 1013-1016. DOI=

Research Resources[1]

Related Conferences
  1. • International Conference on Ubiquitous Computing (UbiComp),
  2. • 11th International Conference on Human-Computer Interaction with Mobile Devices and Services (MobilHCI 09),
  3. • Eighth International Conference on Pervasive Computing (Pervasive 10),
  4. • 11th International Conference on Mobile Data Manage- ment (MDM 10),
  5. • International Workshop on Mobile Information Retrieval for Future (MIRF),
  6. • International Workshop on Mobile Media Retrieval (MMR 09),
  7. • International Workshop on Mobile Information Retrieval (MobIR 08), MobIR
Related Organizations
  1. • ACM SIGIR, information retrieval;
  2. • ACM SIGMOBILE, mobility of systems, users, data, and computing;
  3. • ACM SIGSPATIAL, applications involving spatial information,