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An Intelligent web pre-fetching Based on Hidden Markov Model

Journal of Donghua University(English Edition) 2004年第1期21卷 46-50页

作者：许欢庆金鑫 Department of Computing Science Shanghai Jiaotong University Shanghai 200030 Institute of Information Science & Technology Donghua University Shanghai 200051eb pre-fetching is one of the most popular strategies which are proposed for reducing the perceived access delay and improving the service quality of web server. In this paper we present a pre-fetching model based an the hidden Markov model which mines the later information requirement concepts that the user's access path contains and makes semantic-based pre-fetching decisions. Experimental results show that our schcme has better predictive pre-fetching precision.

web pre-fetching is one of the most popular strategies, which are proposed for reducing the perceived access delay and improving the service quality of web server. In this paper, we present a pre-fetching model based an the hidden Markov model, which mines the later information requirement concepts that the user's access path contains and makes semantic-based pre-fetching decisions. Experimental results show that our schcme has better predictive pre-fetching precision.

关键词： web pre-fetching hidden Markov model information requirement concept

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Meaningless to Meaningful web Log Data for Generation of web pre-caching Decision Rules Using Rough Set

Meaningless to Meaningful Web Log Data for Generation of Web...

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4th Conference on Data Mining and Optimization (DMO)

作者： Sulaiman, Sarina Shamsuddin, Siti Mariyam Ahmad, Nor Bahiah Abraham, Ajith Univ Teknol Malaysia Fac Comp Sci & Informat Syst Soft Comp Res Grp Johor Baharu Malaysia MIR Labs Washington DC 98092 USA

ISBN: (纸本)9781467327183

web caching and pre-fetching are vital technologies that can increase the speed of web loading processes. Since speed and memory are crucial aspects in enhancing the performance of mobile applications and websites, a better technique for web loading process should be investigated. The weaknesses of the conventional web caching policy include meaningless information and uncertainty of knowledge representation in web logs data from the proxy cache to mobile-client. The organisation and learning task of the knowledge-processing for web logs data require explicit representation to deal with uncertainties. This is due to the exponential growth of rules for finding a suitable knowledge representation from the proxy cache to the mobile-client. Consequently, Rough Set is chosen in this research to generate web pre-caching decision rules to ensure the meaningless web log data can be changed to meaningful information.

关键词： component decision rules rough set web caching web pre-fetching web log data

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Semantics-based pre-fetching for reducing WWW latency

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Chinese Journal of Systems Engineering and Electronics 2004年第4期000卷

A semantics-based pre-fetching model is presented. This model predicts future requests based on latent intention that the user's current access path implies in semantics, rather than on temporal relationships, which oversomes the limitation of previous pre-fetching approaches. The hidden Markov model (HMM) was employed for mining actual intention from access patterns. Experimental results show that the proposed pre-fetching model has better general performance.

关键词： web pre-fetching latent intention hidden Markov model

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