Skip to main content

A Framework to Collect and Visualize User’s Browser History for Better User Experience and Personalized Recommendations

  • Conference paper
  • First Online:
Information and Communication Technology for Intelligent Systems (ICTIS 2017) - Volume 1 ( ICTIS 2017)

Abstract

In all the modern browsers, maintaining user’s web history is one of the primary tasks. Browser history will help to summarize the activity of the user during a certain period. However, current browser history is not so efficient to visualize in a user-friendly manner and also doesn’t provide enough information for personalized recommendations. One of the key reason is that browsers never maintain any inter-connection between history items. Overall history is maintained in a linear fashion with no information about how the user reached to a particular state. Another issue is that it is not possible to calculate how much time the user spent on any particular website using current history system. This paper provides a conceptual idea of solving these issues by providing a framework that solves this issue by introducing linked data and also describes how this can benefit in improving user experience and quality of recommendations.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
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. Jany Shabu, S.L., Manoj Kumar, K.: Preserving user’s privacy in personalized search. Int. J. Appl. Eng. Res. (IJAER) 9(22), 16269–16276 (2014). ISSN/E-ISSN: 0973-4562/1087-1090

    Google Scholar 

  2. Manoj Kumar, K., Vikram, M.: Disclosure of user’s profile in personalized search for enhanced privacy. Int. J. Appl. Eng. Res. (IJAER) 10(16), 37261–37266 (2015). ISSN/E-ISSN: 0973-4562/1087-1090

    Google Scholar 

  3. Manoj Kumar, K., Tejasree, S., Swarnalatha, S.: Effective implementation of data segregation & extraction using big data in E-health insurance as a service. In: 2016 3rd International Conference on Advanced Computing and Communication Systems (ICACCS), Coimbatore, pp. 1–5 (2016)

    Google Scholar 

  4. Praveen Kumar, R., Manoj Kumar, K., Tejasree, S., Aswini, R.: Review on cost effective and dynamic security provision strategy of staging data items in cloud. Res. J. Pharm. Biol. Chem. Sci. (RJPBCS) 7(6), 1592–1597 (2016). ISSN: 0975-8585

    Google Scholar 

  5. Ter Louw, M., Lim, J.S., Venkatakrishnan, V.N.: Extensible web browser security. In: International Conference on Detection of Intrusions and Malware, and Vulnerability Assessment, pp. 1–19. Springer, Heidelberg (2007)

    Google Scholar 

  6. Jang-Jaccard, J., Nepal, S.: A survey of emerging threats in cybersecurity. J. Comput. Syst. Sci. 80(5), 973–993 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  7. Wang, L., Xiang, J., Jing, J., Zhang, L.: Towards fine-grained access control on browser extensions. In: International Conference on Information Security Practice and Experience, pp. 158–169. Springer, Heidelberg (2012)

    Google Scholar 

  8. Isinkaye, F.O., Folajimi, Y.O., Ojokoh, B.A.: Recommendation systems: principles, methods and evaluation. Egypt. Inf. J. 16(3), 261–273 (2015)

    Article  Google Scholar 

  9. Rouzbeh, M., Davis, J.G.: Recommendations using linked data. In: Proceedings of the 5th PhD Workshop on Information and Knowledge, 02 November (2012)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to K. Manoj Kumar .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG

About this paper

Cite this paper

Kandala, H., Tripathy, B.K., Manoj Kumar, K. (2018). A Framework to Collect and Visualize User’s Browser History for Better User Experience and Personalized Recommendations. In: Satapathy, S., Joshi, A. (eds) Information and Communication Technology for Intelligent Systems (ICTIS 2017) - Volume 1. ICTIS 2017. Smart Innovation, Systems and Technologies, vol 83. Springer, Cham. https://doi.org/10.1007/978-3-319-63673-3_26

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-63673-3_26

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-63672-6

  • Online ISBN: 978-3-319-63673-3

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics