Skip to main content
SpringerLink
Log in

Context-Aware Computing and Personalization

  • Chapter
  • First Online:
Context-Aware Pervasive Systems and Applications

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 169))

Abstract

User modelling plays the main role to support an individual user to improve in his/her working experience, learning methods and information access. In the new generation of pervasive and context-aware systems, contextualized and personalized information and services are the driving entities. This chapter explains how context-aware computing is important for personalization. The relationship between machine learning, ontology learning and personalization is also discussed in this chapter. The next part of this chapter focuses on context-aware profiling and profile translation towards context-aware services. The need for clustering in ubiquitous computing and how context-aware clustering will play an important role in the next-generation Internet is discussed in the last part of this chapter.

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 49.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 64.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 99.99
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

References

  1. Dominic, S.: The Modern Algebra of Information Retrieval. The Information Retrieval Series. Springer, Berlin (2008)

    Google Scholar 

  2. Finkelstein, L., Gabrilovich, E., Matias, Y., Rivlin, E., Solan, Z., Wolfman, G., Ruppin, E.: Placing search in context: the concept revisited. In: WWW, pp. 406–414 (2001)

    Google Scholar 

  3. Schilit, W.N., Adams, N.I., Want, R.: Context-aware computing applications. In: Proceedings of the Workshop on Mobile Computing Systems and Applications, Santa Cruz, California, pp. 85–90. IEEE Computer Society Press (1994)

    Google Scholar 

  4. Jones, G.: Challenges and opportunities of context-aware information access. In: UDM’05: Proceedings of the International Workshop on Ubiquitous Data Management, pp. 53–62, Washington, DC, USA. IEEE Computer Society (2005)

    Google Scholar 

  5. Gruber, T.R.: A translation approach to portable ontology specification. Knowl. Acquis. 5, 199–220 (1993)

    Article  Google Scholar 

  6. McGuinness, D.L., Fikes, R., Rice, J., Wilder, S.: An environment for merging and testing large ontologies. In: Cohn, A.G., Giunchiglia, F., Selman, B. (eds.) Proceedings of the Seventh International Conference on Principles of Knowledge Representation and Reasoning (KR2000). Morgan Kaufmann Publishers, San Francisco, CA (2000)

    Google Scholar 

  7. G’abor, N.: Ontology development. In: Studer, R., Grimm, S., Abecker, A. (eds.) Semantic Web Services. Springer, Berlin, Heidelberg (2007)

    Google Scholar 

  8. Noy, N.F., McGuinness, D.L.: Ontology Development 101: A Guide to Creating Your First Ontology, 94305. Stanford University, Stanford, CA

    Google Scholar 

  9. Wang, X.H., Zhang, D.Q., Gu, T., Pung, H.K.: Ontology based context modelling and reasoning using OWL. In: Proceedings of 2nd IEEE Conference on Pervasive Computing and Communications (PerCom 2004), Workshop on Context Modeling and Reasoning, pp. 18–22, Orlando, Florida, Mar 2004. IEEE Computer Society Press (2004)

    Google Scholar 

  10. Lehmann, J., Hitzler, P.: A refinement operator based learning algorithm for the ALC description logic. In: Proceedings of the 17th International Conference on Inductive Logic Programming (ILP). Springer, Berlin (2007)

    Google Scholar 

  11. Dellschaft, K.: Measuring the similarity of concept hierarchies and its influence on the evaluation of learning procedures. Master’s thesis, Universität Koblenz Landau, Campus Koblenz, Fachbereich 4 Informatik, Institut für Computervisualisitk (2005)

    Google Scholar 

  12. Sarma, A., Girao, J.: Identities in the future internet of things. Wirel. Pers. Commun. 49, 353–363 (2009). © Springer Science+Business Media, LLC. 200 Tuesday, 07 Apr 2009

    Article  Google Scholar 

  13. GPP TS 23.127: Service aspects; The Virtual Home Environment

    Google Scholar 

  14. Olsen, R.L., Nickelsen, A., Nielsen, J., Schwefel, H.P., Bauer, M.: Experimental analysis of the influence of context awareness on service discovery in PNs. In: Proceedings of IST Summit 2006, Mykonos, Greece (2006)

    Google Scholar 

  15. Sun, X., May, A.: The role of spatial contextual factors in mobile personalization at large sports events. Pers. Ubiquitous Comput. 13, 293–302 (2009). https://doi.org/10.1007/s00779-008-0203-6

    Article  Google Scholar 

  16. Suh, Y., Shin, C., Woo, W.: A mobile phone guide: spatial, personal, and social experience for cultural heritage. IEEE Trans. Consum. Electron. 55(4), 2356–2364 (2009). https://doi.org/10.1109/TCE.2009.5373810

    Article  Google Scholar 

  17. Jang, S., Woo, W.: Ubi-UCAM: a unified context-aware application model. In: Proceedings of the 4th International and Interdisciplinary Conference on Modeling and Using Context, CONTEXT’03, pp. 178–189. Springer, Berlin, Heidelberg (2003)

    Google Scholar 

  18. Schmidtke, H.R., Woo, W.: Towards ontology-based formal verification methods for context aware systems. In: Tokuda, H., Beigl, M., Brush, A., Friday, A., Tobe, Y. (eds.) Pervasive 2009, pp. 309–326. Springer, Berlin (2009)

    Google Scholar 

  19. Church, K., Smyth, B., Bradley, K., Cotter, P.: A large scale study of European mobile search behaviour. In: Proceedings of the 10th International Conference on Human Computer Interaction

    Google Scholar 

  20. Dey, A.K., Sabler, D., Abowd, G.D.: A contextual framework and a toolkit for supporting the rapid prototyping of context-aware applications. Hum. Comput. Interact. (HCI) J. 16(2–4), 97 (2001)

    Article  Google Scholar 

  21. Abowd, G., Dey, A., Brown, P., Davies, N., Smith, M., Steggles, P.: Towards a better understanding of context and context-awareness. In: Handheld and Ubiquitous Computing, pp. 304–307. Springer, Berlin/Heidelberg (1999)

    Chapter  Google Scholar 

  22. Wei, D., Jin, Y., Vural, S., Moessner, K., Tafazolli, R.: An energy-efficient clustering solution for wireless sensor networks. IEEE Trans. Wirel. Commun. 10(11), 3973–3983 (2011)

    Article  Google Scholar 

  23. Nayak, P., Vathasavai, B.: Genetic algorithm based clustering approach for wireless sensor network to optimize routing techniques. In: 2017 7th International Conference on Cloud Computing, Data Science & Engineering-Confluence, pp. 373–380, Jan 2017

    Google Scholar 

  24. Juneja, P., Jain, H., Deshmukh, T., Somani, S., Tripathy, B.K.: Context aware clustering using glove and K-means. Int. J. Softw. Eng. Appl. 8, 21–38 (2017)

    Google Scholar 

  25. Chiti, F., Fantacci, R., Dei, E., Han, Z.: Context aware clustering in VANETs: a game theoretic perspective. In: 2015 IEEE International Conference on Communications (ICC), pp. 6584–6588, IEEE, June 2015

    Google Scholar 

  26. Abdellatief, W., Youness, O., Abdelkader, H., Hadhoud, M.: Global distributed clustering technique for randomly deployed wireless sensor networks. In: 2016 12th International Computer Engineering Conference (ICENCO), pp. 8–13, IEEE, Dec 2016

    Google Scholar 

  27. Cao, H.H., Zhang, Y.M.: A context-aware member clustering algorithm based on ant colony and genetic optimization for P2P mobile social network. In: Applied Mechanics and Materials, vol. 347, pp. 2458–2462. Trans Tech Publications (2013)

    Google Scholar 

  28. Hoang, D.C., Yadav, P., Kumar, R., Panda, S.K.: Real-time implementation of a harmony search algorithm-based clustering protocol for energy-efficient wireless sensor networks. IEEE Trans. Industr. Inf. 10(1), 774–783 (2014)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Computer Engineering, Shrimati Kashibai Navale College of Engineering, Pune, Maharashtra, India

    Parikshit N. Mahalle

  2. Computer Engineering, Dr. D. Y. Patil Institute of Technology, Pimpri, Pune, Maharashtra, India

    Prashant S. Dhotre

Authors
  1. Parikshit N. Mahalle
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Prashant S. Dhotre
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Parikshit N. Mahalle .

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Singapore Pte Ltd.

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Mahalle, P.N., Dhotre, P.S. (2020). Context-Aware Computing and Personalization. In: Context-Aware Pervasive Systems and Applications. Intelligent Systems Reference Library, vol 169. Springer, Singapore. https://doi.org/10.1007/978-981-32-9952-8_4

Download citation

  • DOI: https://doi.org/10.1007/978-981-32-9952-8_4

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-32-9951-1

  • Online ISBN: 978-981-32-9952-8

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation