Skip to main content

E-Mail on the Move: Categorization, Filtering, and Alerting on Mobile Devices with the ifMail Prototype

  • Conference paper
Mobile and Ubiquitous Information Access (MUIA 2003)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2954))

Included in the following conference series:

Abstract

We propose an integrated approach to email categorization, filtering, and alerting on mobile devices. After a general introduction to the problem, we present the ifMail prototype, capable of: categorize incoming email messages into pre-defined categories; filter and rank the categorized messages according to their importance; and alert the user on mobile devices when important messages are waiting to be read. The second part of the paper describes an extended evaluation of the ifMail prototype, whose results show the high effectiveness levels reached by the system.

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 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight 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. Androutsopoulos, I., Koutsias, J., Chandrinos, K.V., Paliouras, G., Spyropoulos, C.D.: An Evaluation of Naive Bayesian Anti-Spam Filtering. In: Proceedings of the Workshop on Machine Learning in the New Information Age, 11th European Conference on Machine Learning (ECML), Barcelona, Spain, pp. 9–17 (2000)

    Google Scholar 

  2. Asnicar, F.A., Di Fant, M., Tasso, C.: User Model-Based Information Filtering. In: Lenzerini, M. (ed.) AI*IA 1997. LNCS (LNAI), vol. 1321, pp. 242–253. Springer, Heidelberg (1997)

    Google Scholar 

  3. Brajnik, G., Tasso, C.: A shell for Developing Non-Monotonic User Modeling System. International Journal of Human-Computer Studies 40, 31–62 (1994)

    Article  Google Scholar 

  4. Brutlag, C., Meek, J.: Challenges of the email domain for text classification. In: Proceedings of the Seventeenth International Conference on Machine Learning, pp. 103–110 (2000)

    Google Scholar 

  5. Buchanan, G., Jones, M., Thimbleby, H., Farrant, S., Pazzani, M.: Improving mobile internet usability. In: Proceedings 10th WWW Conf., pp. 673–680. ACM Press, New York (2001)

    Google Scholar 

  6. Carreras, X., Marquez, L.: Boosting Trees for Anti-Spam Email Filtering. In: Proceedings of RANLP-01. 4th International Conference on Recent Advances in Natural Language Processing, Tzigov hark, BG (2001)

    Google Scholar 

  7. Chittaro, L., Dal Cin, P.: Evaluating interface Design Choices on WAP Phones: Navigation and Selection. Personal and Ubiquitous Computing 6(4), 237–244 (2002)

    Article  Google Scholar 

  8. Cohen, W.: Learning Rules that Classify E-Mail. In: Papers from the AAAI Spring Symposium on Machine Learning in Information Access, pp. 18–25 (1996)

    Google Scholar 

  9. Crawford, E., Kay, J., McCreath, E.: Automatic Induction of Rules for e-mail classification. In: Proceedings of the Sixth Australian Document Computing Symposium, Coffs Harbour, Australia, December 7 (2001)

    Google Scholar 

  10. Ducheneaut, N., Bellotti, V.: Email as Habitat. Interactions (September/October 2001)

    Google Scholar 

  11. Jones, M., Buchanan, G., Thimbleby, H.: Sorting out searching on small screen devices. In: Paternó, F. (ed.) Mobile HCI 2002. LNCS, vol. 2411, pp. 81–94. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  12. Mackay, W.: Diversity in the Use of Electronic Mail: A Preliminary Inquiry. ACM Transactions on Office Information Systems 6(4), 380–397 (1988)

    Article  Google Scholar 

  13. Manco, G., Masciari, E., Ruffolo, M., Tagarelli, A.: Towards An Adaptive Mail Classifier. In: Atti dell’Ottavo Convegno AI*IA 2002, Siena, Italy, p. 63 (2002)

    Google Scholar 

  14. McCreath, E., Kay, J.: Iems: Helping Users Manage Email. In: Brusilovsky, P., Corbett, A.T., de Rosis, F. (eds.) UM 2003. LNCS, vol. 2702, pp. 263–272. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  15. Minio, M., Tasso, C.: User Modelling for Information Filtering on Internet Services: Exploiting an Extended Version of the UMT Shell. In: UM 1996 Workshop on “User Modeling for Information Filtering on the WWW”, Kaiula-Kona, Hawaii, USA, January, 2-5 (1996)

    Google Scholar 

  16. Minio, M., Tasso, C.: IFT: un’Interfaccia Intelligente per il Filtraggio di Informazioni Basato su Modellizzazione d’Utente. AI*IA Notizie IX(3), 21–25 (1996)

    Google Scholar 

  17. Mizzaro, S., Tasso, C.: Ephemeral and Persistent Personalization in Adaptive Information Access to Scholarly Publications on the Web. In: De Bra, P., Brusilovsky, P., Conejo, R. (eds.) AH 2002. LNCS, vol. 2347, pp. 306–316. Springer, Heidelberg (2002) ISBN 3-540-43737-1

    Chapter  Google Scholar 

  18. Moulinier, I., Raskinis, G., Ganascia, J.G.: Text Categorization: a Symbolic Approach. In: Proceedings of the Fifth Annual Symposium on Document Analysis and Information Retrieval, Las Vegas, April 1996, pp. 87–99 (1996)

    Google Scholar 

  19. Nokia Corporation, WML to XHTML migration. Version 2.0 (2002), http://www.nokia.com/

  20. Openwave Systems Inc., Openwave Usability Guidelines for WAP Applications (2001), http://developer.openwave.com/support/techlib.html/

  21. Openwave Systems Inc., Migrating to WML with GUI Extensions and XHTML Mobile Profile (2001), http://developer.openwave.com/support/techlib.html/

  22. Open Mobile Alliance, http://www.wapforum.org/

  23. Pantel, P., Lin, D.: Spamcop: A spam classification & organization program. In: Proceedings of AAAI 1998 Workshop on Learning for Text Categorization, pp. 95–98 (1998)

    Google Scholar 

  24. Payne, T., Edwards, P.: Interface agents that learn: An investigation of learning issues in a mail agent interface. Applied Artificial Intelligence 11, 1–32 (1997)

    Article  Google Scholar 

  25. Phone.com Inc., WML Application Style Guide (2000), http://www.openwave.com/

  26. Rennie, J.D.M.: ifile: An application of Machine Learning to E-Mail Filtering. In: Proceedings KDD 2000 Workshop on Text Mining, Boston (2000)

    Google Scholar 

  27. Sahami, M., Dumais, S., Heckerman, D., Horvitz, E.: A bayesian approach to filtering junk e-mail. In: AAAI 1998 Workshop on Learning for Text Categorization (1998)

    Google Scholar 

  28. Sebastiani, F.: Machine Learning in Automated Text Categorization. ACM Computing Surveys 34(1), 1–47 (2002)

    Article  Google Scholar 

  29. Segal, R.B., Kephart, J.O.: Incremental Learning in SwiftFile. In: Proceeding of the International Conference on Machine Learning, pp. 863–870. IBM, San Francisco (2000)

    Google Scholar 

  30. Tasso, C., Armellini, M.: Exploiting User Modeling Techniques in Integrated Information Services: The TECHFINDER System. In: Lamma, E., Mello, P. (eds.) Proceedings of the 6th Congress of the Italian Association for Artificial Intelligence, Pitagora Editrice, Bologna, I, September 14-17, pp. 519–522 (2000)

    Google Scholar 

  31. Van Rijsbergen, K.: Information Retrieval, 2nd edn. Butterworths, London (1979), http://www.dcs.gla.ac.uk/Keith/pdf

  32. Venolia, G., Dabbish, L., Cadiz, J.J., Gupta, A.: Supporting Email Workflow. Microsoft Research Tech Report MSR-TR-2001-88

    Google Scholar 

  33. Whittaker, S., Sidner, C.: Email Overload: Exploring Personal Information Management of Email. In: Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI 1996), pp. 276–283 (1996)

    Google Scholar 

  34. Yang, Y., Liu, X.: A re-examination of text categorization methods. In: Proceedings of the 22nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Berkley, CA, USA, August 15-19, pp. 42–49 (1999)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2004 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Cignini, M., Mizzaro, S., Tasso, C., Virgili, A. (2004). E-Mail on the Move: Categorization, Filtering, and Alerting on Mobile Devices with the ifMail Prototype. In: Crestani, F., Dunlop, M., Mizzaro, S. (eds) Mobile and Ubiquitous Information Access. MUIA 2003. Lecture Notes in Computer Science, vol 2954. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24641-1_9

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-24641-1_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-21003-0

  • Online ISBN: 978-3-540-24641-1

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics