Web prefetching is a key technology to hide network latencies from users. Conventional prefetching methods, however, misconstrue the purpose of user's browsing behaviors and resulting experience due to their dependence on statistical characteristics or metadata of individual Web applications. In this letter, we propose a predictive prefetching scheme, WebPrefetcher, which utilizes interaction events to decipher user's genuine intention and context. Our intensive performance analysis results obtained with a real Web browser demonstrate that WebPrefetcher improves user-perceived quality of experience noticeably, outperforming competitive models.
- Web prefetching
- quality of experience
- user interaction
ASJC Scopus subject areas
- Modelling and Simulation
- Computer Science Applications
- Electrical and Electronic Engineering