Mining web usage data for real-time online recommendation
Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45) › 32_Refereed conference paper (with ISBN/ISSN) › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
| Original language | English |
|---|---|
| Title of host publication | ICEIS 2003 - Proceedings of the 5th International Conference on Enterprise Information Systems |
| Publisher | Escola Superior de Tecnologia do Instituto Politecnico de Setubal |
| Pages | 575-578 |
| Volume | 2 |
| ISBN (Print) | 9729881618 |
| Publication status | Published - 2003 |
Publication series
| Name | |
|---|---|
| Volume | 2 |
Conference
| Title | 5th International Conference on Enterprise Information Systems, ICEIS 2003 |
|---|---|
| Place | France |
| City | Angers |
| Period | 23 - 26 April 2003 |
Link(s)
Abstract
Web usage data contains a lot of information about the relationship between web pages and users. Investigating this information may provide better knowledge about the user's online behaviours. In this paper, an online recommendation model is proposed based on the web usage data. First users are classified using a back propagation neural network algorithm. Then, within each group, an association rules algorithm is employed to discover common user profiles. Finally, recommendation sets are generated based on the user's active session.
Research Area(s)
- Active session, Association rule, Back propagation neural network (BPNN), Log file
Citation Format(s)
Mining web usage data for real-time online recommendation. / Wang, Mo; Rees, S. J.; Liao, S. Y. et al.
ICEIS 2003 - Proceedings of the 5th International Conference on Enterprise Information Systems. Vol. 2 Escola Superior de Tecnologia do Instituto Politecnico de Setubal, 2003. p. 575-578.Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45) › 32_Refereed conference paper (with ISBN/ISSN) › peer-review
