Abstract
With the development of computer technology and the popularity of the Internet, Web data breaks through the limitations of traditional data formats, and it becomes more and more important, becoming an effective way for Web users to better obtain information. Web log data is data that records user access information to Web sites, stores a large amount of path information, and user access patterns obtained by mining these log information, in personalized information services, improved portal site design and services, and targeted E-commerce, building intelligent Web sites and improving the reputation and effectiveness of the site will play an important role. However, due to the particularity of Web data and applications, traditional mining techniques cannot be directly applied to Web mining. This paper first preprocessing the Web Log data through a real estate Web site, after cleaning and deleting invalid data, by using the method of simple association rule to find the characteristics of the user’s search behavior, thereby providing relevant suggestions to the Web site and improving the user experience of the Web site.
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Acknowledgements
This work is support by “The Second Batch of Young and Middle-aged Research Scientists” of Nantong Institute of Technology (Grant No. ZQNGG206), the Philosophy and Social Science Fund of Jiangsu Provincial Department of Education (Grant No. 2018SJA1287), and the 13th Five-Year Plan of Jiangsu Province “Key Construction Discipline Project of Business Administration Level 1” (SJY201609).
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Li, C., Li, Y., Yang, Y., Deng, Y. (2020). Analysis of Web Log Mining Based on Association Rule. In: Yang, CT., Pei, Y., Chang, JW. (eds) Innovative Computing. Lecture Notes in Electrical Engineering, vol 675. Springer, Singapore. https://doi.org/10.1007/978-981-15-5959-4_81
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DOI: https://doi.org/10.1007/978-981-15-5959-4_81
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