Comparative evaluation of personalization algorithms for content recommendation

Carlos R. C. Alves, Lúcia V. L. Filgueiras

Abstract

Personalization techniques that combine user characteristics, user behavior, and content organization can be used to help users on finding objectively content on the web. The main contribution of this text is the multidisciplinary study that was conducted integrating different areas on human knowledge in order to find the best way to direct content, including some wide research on personalization concepts and applications. This study also presents the development of the Argo software which is formed by a web site, a component that captures and stores information about the user navigation, and three different personalization algorithms. Using navigation data it is possible to generate user profile, which is used to recommend content. Tests were conducted to check efficiency of the personalization algorithms.

References

  1. Adomavicius, G., Tuzhilin, A. Using data mining methods to build customer profiles. Computer 34, 2 (2001), 74-82.
  2. Albanese, M., Picariello, A., Sansone, C., Sansone, L. Web personalization: Web personalization based on static information and dynamic user behavior. Proceedings of the 6th annual ACM international workshop on Web information and data management (2004), 80-87.
  3. Ardissono, L., Goy, A., Petrone, G., Segnan, M. A multi-agent infrastructure for developing personalized web-based systems. ACM Transactions on Internet Technology - TOIT 5, 1 (2005), 47-69.
  4. Ardissono, L. et al. Intrigue: personalized recommendation of tourist attractions for desktop and handset devices. Applied Artificial Intelligence (2002).
  5. Bauer, T., Leake, D. Using document access sequences to recommend customized information. IEEE Intelligent Systems 17, 6 (2002), 27-33.
  6. Cannataro, M., Cuzzocrea, A., Pugliese, A. A probabilistic adaptive hypermedia system. Proceedings of international conference on information technology: coding and computing (2001), 411-415.
  7. Chen, C.C., Chen, M.C., Sun, Y. PVA: a self-adaptive personal view agent system. Proceedings of ACM SIGKDD international conference on knowledge discovery and data mining (2001), 257-262.
  8. Eirinaki, M., Charalampos, L., Stratos, P., Vazirgiannis. Web personalization integrating content semantics and navigational patterns. Proceedings of the 6th annual ACM international workshop on Web information and data management (2004), 72-79.
  9. Genesereth, M.R., Nilsson, N.J. Logical foundations of artificial intelligence. Morgan Kauffman Publishers (1987).
  10. Hackos, J.T., Redish, J.C. User and task analysis for interface design. John Wiley & Sons (1998).
  11. Hölscher, C., Strube, G. Web search behavior of internet experts and newbies. Computer networks 33 (2000), 337-346.
  12. Jokela S. et al. The role of structured content in personalized news service. Proceedings of the 34th Hawaii International conference on systems sciences (2001).
  13. Lin, R., Kraus, S., Tew, J. OSGS-A personalized online store for e-commerce environments. Information retrieval 7, Kluwer Academic Publishers (2004), 369-394.
  14. Menczer, F., Street, W.N., Monge, A.E. Adaptive assistants for customized e-shopping. IEEE Intelligent Systems 17, 6 (2002), 12-19.
  15. Mobasher B. et al. Integrating web usage and content mining for more effective personalization. Electronic commerce and web technologies 1875 (2000), 165-176.
  16. Padmanabhan, B., Zheng, Z., Kimbrough, S.O. Personalization from incomplete data: what do you don't know can hurt. ACM SIGKDD international conference on knowledge discovery and data mining (2001), 154-163.
  17. Perkowitz, M., Etzioni, O. Towards adaptive web sites: conceptual framework and case study. Computer networks 31 (1999), 1245-1258.
  18. Ramakrishnan, N. PIPE: Web personalization by partial evaluation. IEEE internet computing 4, 6 (2000), 21-31.
  19. Sae-Tang, S., Esichaikul, V. Web personalization techniques for e-commerce. Proceedings of the 6th international computer science conference. Springer-Verlag (2001), 36-44.
  20. Smyth, B., Cotter, P. A personalized television listings service. Communications of the ACM 43, 8 (2000), 107-111.
  21. Soltysiak, S.J., Crabtree, I.B. Automatic learning of user profiles - towards the personalization of agent services. BT Technology Journal 16, 3 (1998), 110-117.
Download


Paper Citation


in Harvard Style

R. C. Alves C. and V. L. Filgueiras L. (2005). Comparative evaluation of personalization algorithms for content recommendation . In Proceedings of the 1st International Workshop on Web Personalisation, Recommender Systems and Intelligent User Interfaces - Volume 1: WPRSIUI, (ICETE 2005) ISBN 972-8865-38-4, pages 56-65. DOI: 10.5220/0001421900560065


in Bibtex Style

@conference{wprsiui05,
author={Carlos R. C. Alves and Lúcia V. L. Filgueiras},
title={Comparative evaluation of personalization algorithms for content recommendation},
booktitle={Proceedings of the 1st International Workshop on Web Personalisation, Recommender Systems and Intelligent User Interfaces - Volume 1: WPRSIUI, (ICETE 2005)},
year={2005},
pages={56-65},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001421900560065},
isbn={972-8865-38-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 1st International Workshop on Web Personalisation, Recommender Systems and Intelligent User Interfaces - Volume 1: WPRSIUI, (ICETE 2005)
TI - Comparative evaluation of personalization algorithms for content recommendation
SN - 972-8865-38-4
AU - R. C. Alves C.
AU - V. L. Filgueiras L.
PY - 2005
SP - 56
EP - 65
DO - 10.5220/0001421900560065