Mining Web usage using FRS
Web Usage Mining (WUM) is the application of data mining methods in extracting potentially useful information from web usage data. Its application includes improving website design, personalised service, target marketing etc. Among the outstanding research issues in WUM include inefficiency in minin...
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| Main Authors: | , |
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| Format: | Conference or Workshop Item |
| Language: | English English English |
| Published: |
Institute of Electrical and Electronics Engineers Inc.
2018
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| Online Access: | http://irep.iium.edu.my/72767/1/72767_Mining%20Web%20Usage%20Using%20FRS.pdf http://irep.iium.edu.my/72767/2/72767_Mining%20Web%20Usage%20Using%20FRS_SCOPUS.pdf http://irep.iium.edu.my/72767/3/72767_Mining%20Web%20Usage%20Using%20FRS_WOS.pdf http://irep.iium.edu.my/72767/ https://ieeexplore.ieee.org/document/8567138 |
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| Summary: | Web Usage Mining (WUM) is the application of data mining methods in extracting potentially useful information from web usage data. Its application includes improving website design, personalised service, target marketing etc. Among the outstanding research issues in WUM include inefficiency in mining large weblogs, extracted patterns that are not representative of actual user behavior, and mining results which are too general, uninteresting and lack insights. This paper attempts to address the above problems using a method of mining that captures user traversing activities more effectively based on the notion of regularity. A mining algorithm is introduced using the approach of vertical database. The experiments suggest that the method is efficient, scalable, and able to address confusion caused by large number of extracted patterns. |
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