Abstract
Sequential pattern mining is an important data mining problem with broad applications. Especially, it is also an interesting problem in virtual environments. In this paper, we propose a projection-based, sequential patterngrowth approach, called PrefixUnion. Meanwhile, we also introduce the relationships among transactions, views and objects. According to these relationships, we suggest two mining criteria — inter-pattern growth and intra-pattern growth, which utilize these characteristics to offer ordered growth and reduced projected database. As a result, the large-scale VRML models could be accessed more efficiently, allowing for a real-time walk-through in the scene.
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Keywords
- Virtual Environment
- Sequential Pattern
- Sequential Pattern Mining
- Minimum Support Threshold
- Traversal Path
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Hung, SS., Kuo, TC., Liu, D.SM. (2005). PrefixUnion: Mining Traversal Patterns Efficiently in Virtual Environments. In: Sunderam, V.S., van Albada, G.D., Sloot, P.M.A., Dongarra, J. (eds) Computational Science – ICCS 2005. ICCS 2005. Lecture Notes in Computer Science, vol 3516. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11428862_117
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DOI: https://doi.org/10.1007/11428862_117
Publisher Name: Springer, Berlin, Heidelberg
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