Skip to main content
SpringerLink
Log in

Context-Aware Advertising in Pervasive Computing Environment

  • Chapter
Electronic Business and Marketing

Part of the book series: Studies in Computational Intelligence ((SCI,volume 484))

  • 1847 Accesses

Abstract

Due to the recent advances in sensing and wireless communication technologies, we have been able to capture and understand real-world phenomena by employing tiny ubiquitous sensors such as accelerometers, thermometers, and RFID tags installed in daily environments. For example, by attaching ubiquitous sensors to various indoor objects and furniture, we can observe their use and phenomena that occur around them. Real world context information obtained from the ubiquitous sensors has triggered a wide range of applications in, for example, context-aware systems, lifelogging, and monitoring. This article describes a new type of context-aware advertising that employs context information obtained by ubiquitous sensors. We also introduce examples of context-aware advertising on our lifelogging and recommender systems.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Adomavicius, G., Sankaranarayanan, R., Sen, S., Tuzhilin, A.: Incorporating contextual information in recommender systems using a multidimensional approach. ACM Transactions on Information Systems (TOIS) 23(1), 103–145 (2005)

    Article  Google Scholar 

  2. Baeza-Yates, R., Ribeiro-Neto, B.: Modern information retrieval. Addison-Wesley (1999)

    Google Scholar 

  3. Bahl, P., Padmanabhan, V.: RADAR: An in-building RF-based user location and tracking system. In: IEEE INFOCOM 2000, vol. 2, pp. 775–784 (2000)

    Google Scholar 

  4. Bao, L., Intille, S.S.: Activity recognition from user-annotated acceleration data. In: Ferscha, A., Mattern, F. (eds.) PERVASIVE 2004. LNCS, vol. 3001, pp. 1–17. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  5. Blum, M., Pentland, A., Tröster, G.: Insense: Interest-based life logging. IEEE Multimedia 13(4), 40–48 (2006)

    Article  Google Scholar 

  6. Clarkson, B., Mase, K., Pentland, A.: Recognizing user context via wearable sensors. In: Int’l Symp. on Wearable Computers, pp. 69–75 (2000)

    Google Scholar 

  7. Dhar, S., Varshney, U.: Challenges and business models for mobile location-based services and advertising. Communications of the ACM 54(5), 121–128 (2011)

    Article  Google Scholar 

  8. Gemmell, J., Bell, G., Lueder, R., Drucker, S., Wong, C.: MyLifeBits: Fulfilling the Memex vision. In: ACM Multimedia 2002, pp. 235–238 (2002)

    Google Scholar 

  9. Hair, J., Anderson, R., Tatham, R., Black, W.: Multivariate data analysis

    Google Scholar 

  10. Hodge, V., Austin, J.: A survey of outlier detection methodologies. Artificial Intelligence Review 22(2), 85–126 (2004)

    Article  MATH  Google Scholar 

  11. Huang, Z., Zeng, D., Chen, H.: A comparison of collaborative-filtering recommendation algorithms for e-commerce. IEEE Intelligent Systems 22(5), 68–78 (2007)

    Article  Google Scholar 

  12. Ishii, H., Ren, S., Frei, P.: Pinwheels: Visualizing information flow in an architectural space. In: CHI 2001 Extended Abstracts, pp. 111–112 (2001)

    Google Scholar 

  13. Jain, A., Chang, E., Wang, Y.: Adaptive stream resource management using Kalman filters. In: SIGMOD Conference 2004, pp. 11–22 (2004)

    Google Scholar 

  14. Kraft, R., Stata, R.: Finding buying guides with a web carnivore. In: 1st Latin American Web Congress (LA-WEB), pp. 84–92 (2003)

    Google Scholar 

  15. Kurkovsky, S., Harihar, K.: Using ubiquitous computing in interactive mobile marketing. Personal and Ubiquitous Computing 10(4), 227–240 (2006)

    Article  Google Scholar 

  16. LaMarca, A., Chawathe, Y., Consolvo, S., Hightower, J., Smith, I., Scott, J., Sohn, T., Howard, J., Hughes, J., Potter, F., Tabert, J., Powledge, P.S., Borriello, G., Schilit, B.N.: Place lab: Device positioning using radio beacons in the wild. In: Gellersen, H.-W., Want, R., Schmidt, A. (eds.) PERVASIVE 2005. LNCS, vol. 3468, pp. 116–133. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  17. Langheinrich, M., Nakamura, A., Abe, N., Kamba, T., Koseki, Y.: Unintrusive customization techniques for web advertising. Computer Networks 31(11), 1259–1272 (1999)

    Article  Google Scholar 

  18. Lester, J., Choudhury, T., Borriello, G.: A practical approach to recognizing physical activities. In: Fishkin, K.P., Schiele, B., Nixon, P., Quigley, A. (eds.) PERVASIVE 2006. LNCS, vol. 3968, pp. 1–16. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  19. Linden, G., Smith, B., York, J.: Amazon.com recommendations: Item-to-item collaborative filtering. IEEE Internet Computing 7(1), 76–80 (2003)

    Article  Google Scholar 

  20. Liu, H., Shah, S., Jiang, W.: On-line outlier detection and data cleaning. Computers & Chemical Engineering 28(9), 1635–1647 (2004)

    Article  Google Scholar 

  21. Lukowicz, P., Junker, H., Stäger, M., von Büren, T., Tröster, G.: WearNET: A distributed multi-sensor system for context aware wearables. In: Borriello, G., Holmquist, L.E. (eds.) UbiComp 2002. LNCS, vol. 2498, pp. 361–370. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  22. Lukowicz, P., Ward, J.A., Junker, H., Stäger, M., Tröster, G., Atrash, A., Starner, T.: Recognizing workshop activity using body worn microphones and accelerometers. In: Ferscha, A., Mattern, F. (eds.) PERVASIVE 2004. LNCS, vol. 3001, pp. 18–32. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  23. Maekawa, T., Kishino, Y., Sakurai, Y., Suyama, T.: Recognizing the use of portable electrical devices with hand-worn magnetic sensors. In: Lyons, K., Hightower, J., Huang, E.M. (eds.) PERVASIVE 2011. LNCS, vol. 6696, pp. 276–293. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  24. Maekawa, T., Kishino, Y., Yanagisawa, Y., Sakurai, Y.: Mimic sensors: Battery-shaped sensor node for detecting electrical events of handheld devices. In: Kay, J., Lukowicz, P., Tokuda, H., Olivier, P., Krüger, A. (eds.) PERVASIVE 2012. LNCS, vol. 7319, pp. 20–38. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  25. Maekawa, T., Kishino, Y., Yanagisawa, Y., Sakurai, Y.: Recognizing handheld electrical device usage with hand-worn coil of wire. In: Kay, J., Lukowicz, P., Tokuda, H., Olivier, P., Krüger, A. (eds.) PERVASIVE 2012. LNCS, vol. 7319, pp. 234–252. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  26. Maekawa, T., Watanabe, S.: Unsupervised activity recognition with user’s physical characteristics data. In: Int’l Symp. on Wearable Computers, pp. 89–96 (2011)

    Google Scholar 

  27. Maekawa, T., Yanagisawa, Y., Kishino, Y., Ishiguro, K., Kamei, K., Sakurai, Y., Okadome, T.: Object-based activity recognition with heterogeneous sensors on wrist. In: Floréen, P., Krüger, A., Spasojevic, M. (eds.) PERVASIVE 2010. LNCS, vol. 6030, pp. 246–264. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  28. Maekawa, T., Yanagisawa, Y., Kishino, Y., Kamei, K., Sakurai, Y., Okadome, T.: Object-blog system for environment-generated content. IEEE Pervasive Computing 7(4), 20–27 (2008)

    Article  Google Scholar 

  29. Maekawa, T., Yanagisawa, Y., Sakurai, Y., Kishino, Y., Kamei, K., Okadome, T.: Web searching for daily living. In: SIGIR 2009, pp. 27–34 (2009)

    Google Scholar 

  30. Maekawa, T., Yanagisawa, Y., Sakurai, Y., Kishino, Y., Kamei, K., Okadome, T.: Context-aware web search in ubiquitous sensor environment. ACM Transactions on Internet Technology (ACM TOIT) 11(3), 12:1–12:23 (2012)

    Google Scholar 

  31. Markovitch, S., Scott, P.: The role of forgetting in learning. In: ICML 1988, pp. 459–465 (1988)

    Google Scholar 

  32. Matthews, T., Rattenbury, T., Carter, S., Dey, A., Mankoff, J.: A peripheral display toolkit. In: UIST 2004, pp. 247–256 (2004)

    Google Scholar 

  33. McCrickard, D., Chewar, C.: Attentive user interfaces: Attuning notification design to user goals and attention costs. Communications of the ACM 46, 67–72 (2003)

    Article  Google Scholar 

  34. Mihailidis, A., Carmichael, B., Boger, J.: The use of computer vision in an intelligent environment to support aging-in-place, safety, and independence in the home. IEEE Trans. on Info. Tech. BioMedicine 8(3), 238–247 (2004)

    Google Scholar 

  35. Mynatt, E., Rowan, J., Craighill, S., Jacobs, A.: Digital family portraits: Supporting peace of mind for extended family members. In: CHI 2001, pp. 333–340 (2001)

    Google Scholar 

  36. Philipose, M., Fishkin, K., Perkowitz, M.: Inferring activities from interactions with objects. IEEE Pervasive Computing 3(4), 50–57 (2004)

    Article  Google Scholar 

  37. Pousman, Z., Stasko, J.: A taxonomy of ambient information systems: Four patterns of design. In: Int’l Working Conference on Advanced Visual Interfaces (AVI 2006), pp. 67–74 (2006)

    Google Scholar 

  38. Prasithsangaree, P., Krishnamurthy, P., Chrysanthis, P.: On indoor position location with wireless LANs. In: IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, vol. 2, pp. 720–724 (2002)

    Google Scholar 

  39. Ravi, N., Dandekar, N., Mysore, P., Littman, M.: Activity recognition from accelerometer data. In: IAAI 2005, vol. 20, pp. 1541–1546 (2005)

    Google Scholar 

  40. Ribeiro-Neto, B., Cristo, M., Golgher, P., de Moura, E.: Impedance coupling in content-targeted advertising. In: SIGIR 2005, pp. 496–503 (2005)

    Google Scholar 

  41. Salton, G.: Automatic Text Processing. Addison-Wesley (1989)

    Google Scholar 

  42. Shi, Y., Huang, Y., Minnen, D., Bobick, A., Essa, I.: Propagation networks for recognition of partially ordered sequential action. In: CVPR 2004, vol. 2, pp. 862–869 (2004)

    Google Scholar 

  43. Sohn, J., Kim, N., Sung, W.: A statistical model-based voice activity detection. IEEE Signal Processing Letters 6(1), 1–3 (2002)

    Article  Google Scholar 

  44. Tapia, E.M., Intille, S.S., Larson, K.: Activity recognition in the home using simple and ubiquitous sensors. In: Ferscha, A., Mattern, F. (eds.) PERVASIVE 2004. LNCS, vol. 3001, pp. 158–175. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  45. Munguia Tapia, E., Intille, S.S., Larson, K.: Portable wireless sensors for object usage sensing in the home: Challenges and practicalities. In: Schiele, B., Dey, A.K., Gellersen, H., de Ruyter, B., Tscheligi, M., Wichert, R., Aarts, E., Buchmann, A.P. (eds.) AmI 2007. LNCS, vol. 4794, pp. 19–37. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  46. van Dantzich, M., Robbins, D., Horvitz, E., Czerwinski, M.: Scope: Providing awareness of multiple notifications at a glance. In: Int’l Conf. on Advanced Visual Interfaces (AVI 2002), pp. 157–166 (2002)

    Google Scholar 

  47. van Kasteren, T., Noulas, A., Englebienne, G., Kröse, B.: Accurate activity recognition in a home setting. In: Ubicomp 2008, pp. 1–9 (2008)

    Google Scholar 

  48. Wu, J., Osuntogun, A., Choudhury, T., Philipose, M., Rehg, J.: A scalable approach to activity recognition based on object use. In: ICCV 2007, pp. 1–8 (2007)

    Google Scholar 

  49. Yih, W., Goodman, J., Carvalho, V.: Finding advertising keywords on web pages. In: WWW 2006, pp. 213–222 (2006)

    Google Scholar 

  50. Yuan, S., Tsao, Y.: A recommendation mechanism for contextualized mobile advertising. Expert Systems with Applications 24(4), 399–414 (2003)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Graduate School of Information Science and Technology, Osaka University, 2-1 Yamadaoka, Suita, Osaka, 565-0871, Japan

    Takuya Maekawa

Authors
  1. Takuya Maekawa
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Takuya Maekawa .

Editor information

Editors and Affiliations

  1. Technology, Advanced Institute of Industrial, Higashi-Oi 1-10-40, Tokyo, 140-0011, Japan

    Tokuro Matsuo

  2. Universidad Carlos III de Madrid, Av. Universidad 30, Leganés, 28911, Spain

    Ricardo Colomo-Palacios

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Maekawa, T. (2013). Context-Aware Advertising in Pervasive Computing Environment. In: Matsuo, T., Colomo-Palacios, R. (eds) Electronic Business and Marketing. Studies in Computational Intelligence, vol 484. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37932-1_11

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-37932-1_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-37931-4

  • Online ISBN: 978-3-642-37932-1

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation