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A four-gram unified event model for web mining

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Abstract

In order to improve the quality of web data mining algorithm, this paper summarizes the advantages and disadvantages of several web data source models, including web log, application server log, Client-side log, Packet sniffer, and 5-gram united events model. Based on this analysis, a new 4-gram united events model (UEM4) is proposed in this paper. Simulation experiments were conducted to verify the performance of UEM4, compared with web log and 5-gram united events model. The experiment results show that web log has the worst session identification performance; UEM5 has high accuracy, best online and offline performance, but it needs the application system support the ability to identify the session; UEM4 does not require the application system to support session identification, and also has a good accuracy and performance of session identification. Therefore, this model can be used in e-commerce, which can provide high quality data sources for web mining algorithms and improve the quality of intelligent services.

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  1. Mechanical and electrical department, Guangdong AIB Polytechnic College, Guangzhou, 510507, China

    Xinyao Zou

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  1. Xinyao Zou
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Correspondence to Xinyao Zou.

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Zou, X. A four-gram unified event model for web mining. Cluster Comput 21, 967–975 (2018). https://doi.org/10.1007/s10586-017-0988-z

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  • DOI: https://doi.org/10.1007/s10586-017-0988-z

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