Web Usage Mining by Neural Hybrid Prediction with Markov Chain Components

Authors

DOI:

https://doi.org/10.13052/jwe1540-9589.2053

Keywords:

Web prefetching, Webpage prediction, Markov chains, neural networks, browser extension

Abstract

This paper presents and evaluates a two-level web usage prediction technique, consisting of a neural network in the first level and contextual component predictors in the second level. We used Markov chains of different orders as contextual predictors to anticipate the next web access based on specific web access history. The role of the neural network is to decide, based on previous behaviour, whose predictor’s output to use. The predicted web resources are then prefetched into the cache of the browser. In this way, we considerably increase the hit rate of the web browser, which shortens the load times. We have determined the optimal configuration of the proposed hybrid predictor on a real dataset and compared it with other existing web prefetching techniques in terms of prediction accuracy. The best configuration of the proposed neural hybrid method provides an average web access prediction accuracy of 86.95%.

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Author Biography

Arpad Gellert, Computer Science and Electrical Engineering Department, Lucian Blaga University of Sibiu, Romania

Arpad Gellert obtained his MSc (2003) and the PhD (2008) in Computer Science at Lucian Blaga University of Sibiu. He is currently working as an associate professor in the Computer Science and Electrical Engineering Department of the same university. He also worked as visiting researcher in Barcelona and Milano. Previously he was a Java developer at Multimedia Capital Romania. His research interests include computer architecture, smart buildings & factories, web mining and image processing. He published 5 books and over 50 scientific papers in some prestigious journals and international top conferences and acquired more than 300 citations. He was member of several research grants. He developed as a project manager a research grant supported by the Romanian National Council of Academic Research and three internal LBUS grants. Currently he is member of an ongoing Hasso Plattner Excellence Research Grant. He received in 2010 the “Ad Augusta Per Angusta” prize awarded by Lucian Blaga University of Sibiu for excellence in scientific research. His webpage can be found at http://webspace.ulbsibiu.ro/arpad.gellert.

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Published

2021-07-19

Issue

Section

Articles