Abstract
Since the introduction of FP-growth using FP-tree there has been a lot of research into extending its usage to data stream or incremental mining. Most incremental mining adapts the Apriori algorithm. However, we believe that using a tree based approach would increase performance as compared to the candidate generation and testing mechanism used in Apriori. Despite this FP-tree still requires two scans through a dataset. In this paper we present a novel tree structure called Single Pass Ordered Tree SPO-Tree that captures information with a single scan for incremental mining. All items in a transaction are inserted/sorted based on their frequency. The tree is reorganized dynamically when necessary. SPO-Tree allows for easy maintenance in an incremental or data stream environment.
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Koh, Y.S., Dobbie, G. (2011). SPO-Tree: Efficient Single Pass Ordered Incremental Pattern Mining. In: Cuzzocrea, A., Dayal, U. (eds) Data Warehousing and Knowledge Discovery. DaWaK 2011. Lecture Notes in Computer Science, vol 6862. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23544-3_20
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DOI: https://doi.org/10.1007/978-3-642-23544-3_20
Publisher Name: Springer, Berlin, Heidelberg
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