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Dimensionality Reduction using Markov Model for Web Personalisation
VARUN HOODA, MAMTA KATHURIA Department of Computer Engineering, YMCA University of Science and Technology, Faridabad, Haryana, India
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Abstract: One of the important applications of web mining is web personalization. Markov model is quite helpful technique in this regard. But this very model has limitation of large size data requirement and high dimensionality. This paper has efficiently dealt with the problem of high dimensionality in Markov model. Dimensionality is reduced by analyzing the usersโ access behaviour and clustering of web pages based on similar navigational pattern.
Keywords: Web mining, Markov model, Dimensionality, Personalization, Clustering, Analysis.
Keywords: Web mining, Markov model, Dimensionality, Personalization, Clustering, Analysis.
How to Cite:
[1] VARUN HOODA, MAMTA KATHURIA Department of Computer Engineering, YMCA University of Science and Technology, Faridabad, Haryana, India, โDimensionality Reduction using Markov Model for Web Personalisation,โ International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE)
This work is licensed under a Creative Commons Attribution 4.0 International License.