Skip to main content
SpringerLink
Log in

Personalization for unobtrusive service interaction

  • Original Article
  • Published:
Personal and Ubiquitous Computing Aims and scope Submit manuscript

Abstract

Increasingly, mobile devices play a key role in the communication between users and the services embedded in their environment. With ever greater number of services added to our surroundings, there is a need to personalize services according to the user needs and environmental context avoiding service behavior from becoming overwhelming. In order to prevent this information overload, we present a method for the development of mobile services that can be personalized in terms of obtrusiveness (the degree in which each service intrudes the user’s mind) according to the user needs and preferences. That is, services can be developed to provide their functionality at different obtrusiveness levels depending on the user by minimizing the duplication of efforts. On the one hand, we provide mechanisms for describing the obtrusiveness degree required for a service. On the other hand, we make use of Feature Modeling techniques in order to define the obtrusiveness level adaptation in a declarative manner. An experiment was conducted in order to put in practice the proposal and evaluate the user acceptance for the personalization capabilities provided by our approach.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13

Similar content being viewed by others

Notes

  1. http://www.android.com.

  2. http://www.eclipse.org/modeling/m2t.

  3. http://www.eclipse.org/modeling/.

  4. http://www.moskitt.org.

  5. Screenshots of the developed prototype are showed in http://www.pros.upv.es/labs/projects/interactionadaptation.

  6. http://humansystems.arc.nasa.gov/groups/TLX/index.html.

  7. The complete dataset can be downloaded from http://www.pros.upv.es/labs/projects/interactionadaptation.

References

  1. Abrams M, Phanouriou C, Batongbacal AL, Williams SM, Shuster JE (1999) Uiml: an appliance-independent xml user interface language. In: WWW ’99. Elsevier, North-Holland, pp 1695–1708

  2. Ballagas R, Borchers J, Rohs M, Sheridan JG (2006) The smart phone: a ubiquitous input device. IEEE Pervas Comput 5(1):70

    Article  Google Scholar 

  3. Balme L, Demeure A, Barralon N, Coutaz J, Calvary G (2004) Cameleon-rt: a software architecture reference model for distributed, migratable, and plastic user interfaces. In: EUSAI, pp 291–302

  4. Benavides D, Cortés RA, Trinidad P (2005) Automated reasoning on feature models. In: LNCS, advanced information systems engineering: 17th international conference, CAiSE 2005 3520, pp 491–503

  5. Blomquist A, Arvola M (2002) Personas in action: ethnography in an interaction design team. In: Proceedings of NordiCHI ’02. ACM, New York, NY, pp 197–200

  6. Bright A, Kay J, Ler D, Ngo K, Niu W, Nuguid A (2005) Adaptively recommending museum tours. In: Nick Ryan Tullio Salmon Cinotti GR (ed) Proceedings of workshop on smart environments and their applications to cultural heritage. Archaeolingua, pp 29–32

  7. Brown DM (2010) Communicating design: developing web site documentation for design and planning, 2nd edn. New Riders Press, USA

    Google Scholar 

  8. Calvary G, Coutaz J, Thevenin D, Limbourg Q, Bouillon L, Vanderdonckt J (2003) A unifying reference framework for multi-target user interfaces. Interact Comput 15(3):289–308

    Article  Google Scholar 

  9. Cetina C, Giner P, Fons J, Pelechano V (2009) Autonomic computing through reuse of variability models at runtime: the case of smart homes. Computer 42(10):37–43

    Article  Google Scholar 

  10. Chatfield C, Carmichael D, Hexel R, Kay J, Kummerfeld B (2005) Personalisation in intelligent environments: managing the information flow. In: OZCHI ’05. Computer-human interaction special interest group of Australia, pp 1–10

  11. Clerckx T, Winters F, Coninx K (2005) Tool support for designing context-sensitive user interfaces using a model-based approach. In: TAMODIA ’05: Proceedings of the 4th international workshop on Task models and diagrams. ACM Press, New York, pp 11–18

  12. Czarnecki K, Helsen S, Eisenecker U (2004) Staged configuration using feature models. In: Proceedings of SPLC

  13. Duarte C, Carriço L (2006) A conceptual framework for developing adaptive multimodal applications. In: Proceedings of IUI ’06. ACM, New York, pp 132–139

  14. Evans (2003) Domain-driven design: tacking complexity In the heart of software. Addison-Wesley Longman Publishing Co., Inc., Bostons

  15. Favre JM (2004) Foundations of model (Driven) (Reverse) engineering: models—Episode I: stories of the fidus papyrus and of the solarus. In: Bezivin J, Heckel R (eds) Language engineering for model-driven software development, no. 04101, Dagstuhl seminar proceedings. Dagstuhl, Germany

  16. Fischer G (2001) User modeling in human–computer interaction. User Model User-Adap Inter 11(1–2):65–86

    Article  MATH  Google Scholar 

  17. Gibbs WW (2005) Considerate computing. Scientific American 292(1):54–61

    Article  Google Scholar 

  18. Giner P, Cetina C, Fons J, Pelechano V (2010) Developing mobile workflow support in the internet of things. IEEE Pervas Comput 9(2):18–26

    Article  Google Scholar 

  19. Giner P, Cetina C, Fons J, Pelechano V (2011) Implicit interaction design for pervasive workflows. Pers Ubiquit Comput 1–10

  20. Gulliksen J, Goransson B, Boivie I, Blomkvist S, Persson J, Cajander A (2003) Key principles for user-centred systems design. Behav Inform Technol 22:397–409

    Article  Google Scholar 

  21. Hinckley K, Horvitz E (2001) Toward more sensitive mobile phones. In: Proceedings of the UIST ’01. ACM, New York, pp 191–192

  22. Ho J, Intille SS (2005) Using context-aware computing to reduce the perceived burden of interruptions from mobile devices. In: Proceedings of CHI ’05. ACM, New York, pp 909–918

  23. Horvitz E, Kadie C, Paek T, Hovel D (2003) Models of attention in computing and communication: from principles to applications. Commun ACM 46(3):52–59

    Article  Google Scholar 

  24. Ju W, Leifer L (2008) The design of implicit interactions: making interactive systems less obnoxious. Des Issues 24(3):72–84

    Article  Google Scholar 

  25. Lewis JR (1995) Ibm computer usability satisfaction questionnaires: psychometric evaluation and instructions for use. Int J Hum-Comput Interact 7(1):57–78

    Article  Google Scholar 

  26. Limbourg Q, Vanderdonckt J, Michotte B, Bouillon L, López-Jaquero V (2004) Usixml: a language supporting multi-path development of user interfaces. In: EHCI/DS-VIS, pp 200–220

  27. Mao JY, Vredenburg K, Smith PW, Carey T (2001) User-centered design methods in practice: a survey of the state of the art. In: CASCON ’01. IBM Press, New York, p 12

  28. McCrickard DS, Chewar CM (2003) Attuning notification design to user goals and attention costs. Commun ACM 46:67–72

    Article  Google Scholar 

  29. Mori G, Paternò F, Santoro C (2002) Ctte: support for developing and analyzing task models for interactive system design. IEEE Trans Softw Eng 28(8):797–813

    Article  Google Scholar 

  30. Mori G, Paternò F, Santoro C (2004) Design and development of multidevice user interfaces through multiple logical descriptions. IEEE Trans Softw Eng 30(8):507–520

    Article  Google Scholar 

  31. Myers B, Hudson SE, Pausch R (2000) Past, present, and future of user interface software tools. ACM Trans Comput-Hum Interact 7(1):3–28

    Article  Google Scholar 

  32. OMG (2006) Business process modeling notation (BPMN) specification. OMG Final Adopted Specification

  33. Paternò F, Santoro C (2003) A unified method for designing interactive systems adaptable to mobile and stationary platforms. Interact Comput 15(3):349–366

    Article  Google Scholar 

  34. Puerta A, Eisenstein J (2002) Ximl: a common representation for interaction data. In: Proceedings of IUI ’02. ACM, New York, pp 214–215

  35. Ramchurn SD, Deitch B, Thompson MK, Roure DCD, Jennings NR, Luck M (2004) Minimising intrusiveness in pervasive computing environments using multi-agent negotiation. In: First international conference on mobile and ubiquitous systems, pp 364–372

  36. Rumbaugh J, Jacobson I, Booch G (1998) The unified modeling language reference manual. Addison-Wesley, London

    Google Scholar 

  37. Schobbens PY, Heymans P, Trigaux JC, Bontemps Y (2007) Generic semantics of feature diagrams. Comput Networks 51(2):456–479

    Article  MATH  Google Scholar 

  38. Serral E, Pérez F, Valderas P, Pelechano V (2010) An end-user tool for adapting smart environment automation to user behaviour at runtime. In: Proceedings of UCAmI ’10

  39. Streefkerk JW, van Esch-Bussemakers MP, Neerincx MA (2006) Designing personal attentive user interfaces in the mobile public safety domain. Comput Hum Behav 22:749–770

    Article  Google Scholar 

  40. Tedre M (2008) What should be automated? Interactions 15(5):47–49

    Article  Google Scholar 

  41. Unger R, Chandler C (2009) A project guide to UX design: for user experience designers in the field or in the making. New Riders Publishing, Thousand Oaks

    Google Scholar 

  42. Van den Bergh J, Coninx K. Using uml 2.0 and profiles for modelling context-sensitive user interfaces. In: Proceedings of the MDDAUI2005 CEUR workshop

  43. Vastenburg MH, Keyson DV, de Ridder H (2008) Considerate home notification systems: a field study of acceptability of notifications in the home. Pers Ubiquit Comput 12(8):555–566

    Article  Google Scholar 

  44. Vertegaal R (2003) Attentive user interfaces. Commun ACM 46(3):30–33

    Article  Google Scholar 

  45. Weiser M, Brown JS (1997) The coming age of calm technology, pp 75–85

  46. Weld DS, Anderson C, Domingos P, Etzioni O, Gajos K, Lau T, Wolf S (2003) Automatically personalizing user interfaces. In: IJCAI ’03, pp 1613–1619

Download references

Acknowledgments

This work has been developed with the support of MICINN under the project EVERYWARE TIN2010-18011 and co-financed with ERDF, in the grants program FPU.

Author information

Authors and Affiliations

  1. Centro de Investigación en Métodos de Producción de Software, Universitat Politècnica de València, Camino de Vera s/n, 46022, Valencia, Spain

    Miriam Gil, Pau Giner & Vicente Pelechano

Authors
  1. Miriam Gil
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Pau Giner
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Vicente Pelechano
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Miriam Gil.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Gil, M., Giner, P. & Pelechano, V. Personalization for unobtrusive service interaction. Pers Ubiquit Comput 16, 543–561 (2012). https://doi.org/10.1007/s00779-011-0414-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00779-011-0414-0

Keywords

Search

Navigation