PERSONALIZATION IN VIRTUAL ENTERPRISES

Claudio Biancalana, Fabio Gasparetti, Alessandro Micarelli

Abstract

Each business company collects, produces and exploits for its activities and goals large amounts of information. Most of the times this knowledge makes the intellectual capital for creating value and innovation. Knowledge management (KM) systems aim at manipulating knowledge by storing and redistributing corporate information that are acquired from the organizations members. In this context, Virtual Enterprises (VE) plays a crucial role as not permanent alliances of enterprises joined together to share resources and skills in order to better respond to business opportunities. The representation and retrieval of distributed knowledge is an important feature that information systems must provide in order to obtain advantages from this kind of enterprises. PVE (Personalized Virtual Enterprise) is an ongoing research project for developing a system able to extract and let different business companies access to collective knowledge required to achieve particular shared goals. In this paper, we report the most important features of this system, especially in the context of distributed knowledge representation and retrieval.

References

  1. M. Alavi and D.E. Leidner, Review: Knowledge Management and Knowledge Management Systems: Conceptual Foundations and Research Issues. MIS Quarterly, Vol. 25 No. 1, pp. 107-136, 2001.
  2. F. Baader, D. Calvanese, D.L. McGuinness, D. Nardi and P.F. Patel-Schneider (Eds.), The Description Logic Handbook: Theory, Implementation, and Applications. Cambridge University Press, 2003.
  3. P. Brssler, Knowledge Management at a Software Engineering Company - An Experience Report, Workshop on Learning Software Organizations, LSO'99, Kaiserslautern, Germany, pp. 163-170, 1999.
  4. P. Brusilovsky and M. Maybury, From adaptive hypermedia to the adaptive web. Communications of the ACM, Vol. 45 No. 5, pp.3033, 2002.
  5. F. Y. Y. Choi, Advances in domain independent linear text segmentation, In Proc. of the 1st conference on North American chapter of the Association for Computational Linguistics. Seattle, Washington, pp2633, 2000.
  6. C. W. Choo, Information Management for the Intelligent Organization: Roles and Implications for the Information professions. In Proc. of the 1995 Digital Libraries Conference, Singapore, March 1995.
  7. T.H. Davenport and L. Prusak, Working Knowledge: How Organizations Manage What They Know, Harvard Business School Press, 1997.
  8. P. Ferragina and A. Gulli, A personalized search engine based on web-snippet hierarchical clustering. In Proc. Of the 14th World Wide Web Conference, 2005.
  9. G.W. Furnas, T.K. Landauer, L.M. Gomez, and S.T. Dumais, The vocabulary problem in human-system communication. Commun. ACM, Vol. 30 No. 11, pp. 964971, 1987.
  10. B.R. Gaines, M.A. Musen and R. Uthurusamy, Artificial Intelligence in Knowledge Management, Technical Report SS-97-01, Stanford University, 1997.
  11. S. Gauch, M. Speretta, A. Chandramouli and A. Micarelli, User Profiles for Personalized Information Access. In Brusilovsky, P., Kobsa, A., Nejdl, W., eds.: The Adaptive Web: Methods and Strategies of Web Personalization. Volume 4321 of Lecture Notes in Computer Science, pp.54-89. Springer-Verlag, Berlin Heidelberg New York (2007).
  12. A. Gulli and A. Signorini, The indexable web is more than 11.5 billion pages. In the Proc. of the 14th international conference on World Wide Web (WWW05), pp902903, New York, USA, 2005.
  13. R. Hartley, R. Kelsey and R. Webster, Consolidating MultiSource and Multi-Media Knowledge. In AAAI Spring Symposium Articial Intelligence in Knowledge Management. AAAI, March 1997.
  14. N. R. Jennings and M. Wooldridge, Software Agents. IEE Review. Vol. 42 No. 1, pp17-21. January 1996.
  15. T. Joachims, Text categorization with support vector machines: learning with many relevant features. In Proc. of ECML-98, 10th European Conference on Machine Learning, pp.137142, Chemnitz, DE, 1998. Springer Verlag, Heidelberg, DE. Published in the Lecture Notes in Computer Science series, number 1398. 1998.
  16. T. Joachims, Transductive inference for text classification using support vector machines. In Proc. of ICML-99, 16th International Conference on Machine Learning, pp.200209, Bled, SL, 1999. Morgan Kaufmann Publishers, SF, US, 1999.
  17. C. Johansson, C. and P. C. M. Hall, Talk to Paula and Peter - They are Experienced, Workshop on Learning Software Organizations, LSO'99, pp. 171-185, 1999.
  18. D. Kelly and J. Teevan, Implicit feedback for inferring user preference: a bibliography. SIGIR Forum, Vol. 37 No. 2, pp.1828, 2003.
  19. G. Lawton, Knowledge Management: Ready for Prime Time IEEE Computer, Vol. 34, No. 2, pp. 12-14, 2001.
  20. C. Moore, Diving into Data. InfoWorld. October 25, 2002.
  21. I. Nonaka and H. Takeuchi, The Knowledge-Creating Company, Oxford University Press, New York, 1995.
  22. P. Pirolli, P. Schank, M.A. Hearst and C. Diehl, Scatter/Gather Browsing Communicates the Topic Structure of a Very large Text Collection, In Proc. of the ACM SIGCHI Conference on Human Factors in Computing Systems (CHI), May 1996.
  23. G. Salton and M. McGill, An Introduction to modern information retrieval. Mc-Graw-Hill, New York, NY, 1983.
  24. K. Schneider, LIDS: A Light-weight Approach to Experience Elicitation and Reuse, The Profes 2000 Conference, Oulo, Finland, 2000, pp. 407-424, 2000.
  25. K. Schneider, Experience Magnets - Attracting Experiences, Not Just Storing Them, Product Focused Software Process Improvement, PrOFES'01, Kaiserslautern, Germany, pp. 126-140, 2001.
  26. F. Sebastiani, Machine learning in automated text categorization. ACM Computer Surveys. 34(1): 1-47 (2002).
Download


Paper Citation


in Harvard Style

Biancalana C., Gasparetti F. and Micarelli A. (2009). PERSONALIZATION IN VIRTUAL ENTERPRISES . In Proceedings of the Fifth International Conference on Web Information Systems and Technologies - Volume 1: WEBIST, ISBN 978-989-8111-81-4, pages 581-584. DOI: 10.5220/0001842905810584


in Bibtex Style

@conference{webist09,
author={Claudio Biancalana and Fabio Gasparetti and Alessandro Micarelli},
title={PERSONALIZATION IN VIRTUAL ENTERPRISES},
booktitle={Proceedings of the Fifth International Conference on Web Information Systems and Technologies - Volume 1: WEBIST,},
year={2009},
pages={581-584},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001842905810584},
isbn={978-989-8111-81-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Fifth International Conference on Web Information Systems and Technologies - Volume 1: WEBIST,
TI - PERSONALIZATION IN VIRTUAL ENTERPRISES
SN - 978-989-8111-81-4
AU - Biancalana C.
AU - Gasparetti F.
AU - Micarelli A.
PY - 2009
SP - 581
EP - 584
DO - 10.5220/0001842905810584