Skip to main content

A Framework to Infer Webpage Relevancy for a User

  • Conference paper
  • First Online:

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 50))

Abstract

The Web is a vast pool of resources which comprises of a lot of web pages covering all aspects of life. Understanding a user’s interests is one of the major research areas towards understanding the web today. Identifying the relevance of the surfed web pages for the user is a tedious job. Many systems and approaches have been proposed in literature, to try and get information about the user’s interests by user profiling. This paper proposes an improvement in determining the relevance of the webpage to the user, which is an extension to the relevance formula that was proposed earlier. The current work aims to create user profiles automatically and implicitly depending on the various web pages a user browses over a period of time and the user’s interaction with them. This automatically generated user profile assigns weights to web pages proportional to the user interactions on the webpage and thus indicates relevancy of web pages to the user based on these weights.

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

Buying options

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

Learn about institutional subscriptions

References

  1. Faucher, J., McLoughlin, B., Wunschel, J.: Implicit web user interest, Technical Report MQP-CEW-1101, Worcester Polytechnic Institute, Spring (2011)

    Google Scholar 

  2. Hauger, D., Paramythis, A., Weibelzahl, S.: Using browser interaction data to determine page reading behavior. In: UMAP’11, Proceedings of the 19th International Conference on User Modeling, Adaption, and Personalization, pp. 147–158. Girona, Spain, 11–15 July 2011

    Google Scholar 

  3. Kríž, J.: Keyword extraction based on implicit feedback. Inf. Sci. Technol. Bull. ACM Slovakia, 4(2), 43–47

    Google Scholar 

  4. Leiva Torres, L.A., Hernando, R.V.: A gesture inference methodology for user evaluation based on mouse activity tracking. In: IHCI 2008, Proceedings of the IADIS International Conference on Interfaces and Human Computer Interaction, Amsterdam, The Netherlands, 25–27 July 2008

    Google Scholar 

  5. Zahoor, S., Bedekar, M., Kosamkar, P.: User implicit interest indicators learned from the browser on the client side. In: International Conference on Information and Communication Technology for Competitive Strategies, Udaipur, Rajasthan, India, 14–16 Nov 2014

    Google Scholar 

  6. Teevan, J., Dumais, S., Horvitz, E.: Personalizing search via automated analysis of interests and activities. In: Proceedings of the 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ‘05), pp. 449–456. ACM, New York

    Google Scholar 

  7. White, R., Ruthven, I., Jose, J.M.: The use of implicit evidence for relevance feedback in web retrieval. In: Proceedings of the Twenty-Fourth European Colloquium on Information Retrieval Research (ECIR ‘02). Lecture Notes in Computer Science, pp. 93–109. Glasgow (2002)

    Google Scholar 

  8. Shapira, B., Taieb-Maimon, M., Moskowitz, A.: Study of the usefulness of known and new implicit indicators and their optimal combination for accurate inference of users interests. Proceedings of SAC ‘06, pp. 1118–1119

    Google Scholar 

  9. Li, F., Li, Y., Wu, Y., Zhou, K., Li, F., Wang, X.: Discovery of a user interests on the internet. In: Proceedings of the IEEE/WIC/ACM, International Conference on Web Intelligence and Intelligent Agent Technology, pp. 359–362 (2008)

    Google Scholar 

  10. Zahoor, S., Dr. Bedekar, M.: Implicit client side user profiling for improving relevancy if search results, CCSEIT-2014. In: Proceedings of Fourth International Conference on Computational Science, Engineering and Information, Technology, Army Institute of Technology, Pune, India, 8–9 Aug 2014

    Google Scholar 

  11. Zahoor, S., Rajput, D., Bedekar, M., Kosamkar, P.: Capturing, understanding and interpreting user interactions with the browser as implicit interest indicators. In: ICPC 2015, International Conference on Pervasive Computing, Sinhgad College of Engineering, Pune, 8–10 Jan 2015

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Mangesh Bedekar .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Zahoor, S., Bedekar, M., Vishwarupe, V. (2016). A Framework to Infer Webpage Relevancy for a User. In: Satapathy, S., Das, S. (eds) Proceedings of First International Conference on Information and Communication Technology for Intelligent Systems: Volume 1. Smart Innovation, Systems and Technologies, vol 50. Springer, Cham. https://doi.org/10.1007/978-3-319-30933-0_16

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-30933-0_16

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-30932-3

  • Online ISBN: 978-3-319-30933-0

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics