Mining and extracting informative data have been of great interest to researchers
in recent years. One form of extracted information is frequent patterns, which
express the common behaviors that often happen throughout historical records. A
distinct type of such pattern, clickstreams, has emerged due to the Internet and
online commercial business. A simple example is a sequence of web pages that
users often visit, and knowing such behaviors can help website owners customize
their web pages to help improve the user experience or recommend helpful
information. The task of discovering clickstreams can be called clickstream
pattern mining. This work explores some aspects of clickstream pattern mining as
well as the possibilities for improving the performance of algorithms in this topic.
Through the experiments in all 5 cases of study, the thesis’ proposed approaches
were compared with other state-of-the-art methods. They were shown not only
effective and efficient but also faster than the other methods on most test
databases.
| ISBN: | 978-80-7678-357-7 |
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| EAN: | 9788076783577 |
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| Počet stran |
44 stran |
| Datum vydání |
24. 09. 2025 |
| Pořadí vydání |
První |
| Jazyk |
anglický |
| Vazba |
e-kniha - pdf |
| Autor: |
Huy Minh Huynh |
| Nakladatelství |
Univerzita Tomáše Bati ve Zlíně |
| Tématická skupina |
999 - nezařazeno |
| Neprodejná publikace. Publikaci je možné poptávat zde: Volně dostupné na http://hdl.handle.net/10563/56898 |
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