Mining hybrid sequential patterns and sequential rules |
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| Affiliation: | 1. Department of Information Management, National Central University, Chung-Li, Taiwan 320, Republic of China;2. Department of Business Administration, National Central University, Chung-Li, Taiwan 320, Republic of China;1. Vocational School of Health Services, Gumushane University, Gumushane, Turkey;2. Department of Nursing, Eskisehir Osmangazi University, Eskisehir, Turkey;1. Research Department of Oncology, Cancer Institute, Faculty of Medical Sciences, School of Life & Medical Sciences, University College London, London, UK;2. Division of Informatics, Imaging and Data Science, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK;3. Centre for Prognosis Research, School of Primary, Community and Social Care, Keele University, Staffordshire, UK;1. Center for Environmental and Sustainability Research, NOVA School of Science and Technology, NOVA University Lisbon, Portugal;2. Laboratory of Urban Complexity and Sustainability, School of Geography, University of Nottingham, Nottingham, United Kingdom |
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| Abstract: | The problem addressed in this paper is to discover the frequently occurred sequential patterns from databases. Basically, the existing studies on finding sequential patterns can be roughly classified into two main categories. In the first category, the discovered patterns are continuous patterns, where all the elements in the pattern appear in consecutive positions in transactions. The second category is to mine discontinuous patterns, where the adjacent elements in the pattern need not appear consecutively in transactions. Although there are many researches on finding either kind of patterns, no previous researches can find both of them. Neither can they find the discontinuous patterns formed of several continuous sub-patterns. Therefore, we define a new kind of patterns, called hybrid pattern, which is the combination of continuous patterns and discontinuous patterns. In this paper, two algorithms are developed to mine hybrid patterns, where the first algorithm is easy but slow while the second complicated but much faster than the first one. Finally, the simulation result shows that our second algorithm is as fast as the currently best algorithm for mining sequential patterns. |
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