Abstract
The number of people using e-tourism is increasing fast. On the one hand, there are business players who establish their offers in the Web, and on the other hand, there are online tourists who benefit from this large pool of touristic data provided in the tourism platforms. In contrast to traditional tourism selling channels such as travel agencies the relationship between seller and buyer is not really transparent in terms of what does the tourist exactly like and what can the vendor appropriately offer. Web mining and personalization are two common techniques to overcome these limitations. The benefits are two-fold: first, the user will be satisfied because his preferences are respected, and second, innovative business ideas can evolve to increase the return on investment for tourism companies. The paper presented here introduces how to benefit from Web mined data to provide personalization and profitable e-business.
| Original language | English |
|---|---|
| Title of host publication | ENTER 2004, Research Track Support Disk |
| Editors | Andrew J. Frew |
| Publisher | Springer Verlag Wien, New York |
| Number of pages | 12 |
| Publication status | Published - Jan 2004 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 9 Industry, Innovation, and Infrastructure -
SDG 16 Peace, Justice and Strong Institutions
Fields of science
- 102001 Artificial intelligence
- 102006 Computer supported cooperative work (CSCW)
- 102010 Database systems
- 102014 Information design
- 102015 Information systems
- 102016 IT security
- 102028 Knowledge engineering
- 102019 Machine learning
- 102022 Software development
- 102025 Distributed systems
- 502007 E-commerce
- 505002 Data protection
- 506002 E-government
- 509018 Knowledge management
- 202007 Computer integrated manufacturing (CIM)
- 102033 Data mining
- 102035 Data science
Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver