A Trend-based Prediction System for Web User Behavior

淡江大學機構典藏 > 工學院 > 資訊工程學系暨研究所 > 期刊論文 > Item 987654321/17389

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题名:	A Trend-based Prediction System for Web User Behavior
作者:	Jan, Nien-yi;Lin, Shun-chieh;Lin, Nancy P.;Chang, Chung-I
贡献者:	淡江大學資訊工程學系;軍訓室
关键词:	Trend similarity;Prediction system;Web mining;User behavior;Sequence mining
日期:	2008-01
上传时间:	2013-06-07 10:45:10 (UTC+8)
出版者:	Athens: World Scientific and Engineering Academy and Society
摘要:	Since web applications make great progress, the latency of Internet owing to the network bandwidth becomes an urge problem in the cyber world. It is very important to deliberate on how to construct a prediction model to predict web users traveling path for adapting the website structure and improving the website performance. A trend based prediction model without extra information is proposed in this paper to generate prediction models with a sequence of pages for a proxy server prefetcting the suitable pages. The trend similarity is the core of our proposed model which considers not only the page similarity but also position similarity. Two measures include page correctness rate and order correctness rate are proposed to evaluate accuracy of our prediction system.
關聯:	WSEAS Transactions on Advances in Engineering Education 5(1), pp.52-59
显示于类别:	[資訊工程學系暨研究所] 期刊論文

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