| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 552468 | Decision Support Systems | 2008 | 14 Pages |
Websites nowadays are an important and popular source of publicly available information. However, due to their exploding scale and complexity, overcoming information overload to find relevant information is a major challenge. In addition to website maps and search engines, self-adaptive websites or websites with intelligent navigation aid are very useful tools in addressing this issue. In this paper, a navigation graph-based recommendation system is proposed, in which the navigation patterns of previous website visitors are utilized to provide recommendations for newcomers. The performance of the proposed recommendation algorithm is tested using the data collected from a real world website. Experimental results reveal that the proposed system can yield satisfactory recommendations, especially to the visitors in their early navigation steps.
