Predicting web actions from HTML content

Brian D. Davison
2002 Proceedings of the thirteenth ACM conference on Hypertext and hypermedia - HYPERTEXT '02  
Most proposed Web prefetching techniques make predictions based on the historical references to requested objects. In contrast, this paper examines the accuracy of predicting a user's next action based on analysis of the content of the pages requested recently by the user. Predictions are made using the similarity of a model of the user's interest to the text in and around the hypertext anchors of recently requested Web pages. This approach can make predictions of actions that have never been
more » ... ken by the user and potentially make predictions that reflect current user interests. We evaluate this technique using data from a full-content log of Web activity and find that textual similarity-based predictions outperform simpler approaches.
doi:10.1145/513338.513380 dblp:conf/ht/Davison02 fatcat:4twjj55jmvhjdo62lscf7nbrxy