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 pattern-growth 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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