Personalized and artificial intelligence Web caching and prefetching - Acharjee, Utpal (University of Ottawa (Canada), 2006)
Web caching and prefetching are the most popular and widely used solutions to remedy Internet performance problems. Performance is increased if a combination of caching and prefetching systems is used rather than if these techniques are used individually. Web caching reduces the bandwidth consumption and network latency by serving the user's request from its own cache instead of the original Internet source. Prefetching is a technique that preloads and caches the web object that is not currently requested by the user but can be requested (expected) in the near future. It provides low retrieval latency for users and as well as high hit ratios. Existing methods for caching and prefetching are mostly traditional sharable Proxy cache servers. In our personalized caching and prefetching approach, the system builds up a user profile associated with a user's web behaviour by parsing the keywords from HTML pages that are browsed by the user. The keywords of a user profile are updated by adding a new keyword or incrementing its associated weight if it is already, in the profile. This user profile reflects users' web behaviour or interest. In this cache and prefetch prediction module we considered both static and dynamic users' web behaviour. We have designed and implemented an artificial intelligence multilayer neural network-based caching and prediction algorithm to personalize the Proteus Proxy server with this mechanism. Enhanced Proteus is a multilingual and internationally-supported Proxy system and can work with both mobile and traditional Proxy server-based sharable environments. In the prefetch option of Proteus, time also implemented a unique content filtering feature that blocks the downloading of unwanted web objects.
Keywords: Artificial Intelligence.; Computer Science.