Abstract
The key issue of Web prefetching is to establish an effective user prediction model. Prediction by partial match (PPM) is one of the context models used in the Web prefetching area. The high space complexity and low efficiency of the PPM model affect its application. In this paper, we make use of pruning technique and propose a new adaptive PPM model based on Zipf's law and Web access characteristics. The experiments have shown that this model not only can be used to make predictions dynamically, but also has relative lower space complexity and higher prediction accuracy.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
