Mining clickstream patterns using idlists

To date, there remains a lack of works that focus on the problem of mining clickstream patterns. Although it is an alternative to use the general algorithms for sequential pattern mining to mine clickstreams, their performance may suffer and the resources needed are more than necessary. In this paper, we present a novel data structure, called index-IDList, that is suitable for clickstream pattern mining. Based on this data structure, we present a vertical format algorithm named CUI (Clickstream pattern mining Using Index-IDList). The experiments are carried out on four real-life clickstream databases and the results show that our proposed method is effective and efficient in terms of runtimes and memory consumption. © 2019 IEEE.Vietnam National Foundation for Science and Technology Development (NAFOSTED)National Foundation for Science & Technology Development (NAFOSTED); Ministry of Education, Youth and Sports of the Czech Republic within the National Sustainability Programme [LO1303 (MSMT-7778/2014)]; European Regional Development Fund under the Project CEBIA-Tech [CZ.1.05/2.1.00/03.0089]; COST (European Cooperation in Science Technology) [IC1406]; Faculty of Applied Informatics, Tomas Bata University in Zlin (ailab.fai.utb.cz