Abstract
The process of resource distribution and load balance of a distributed P2P network can be described as the process of mining Supplement Frequent Patterns (SFPs) from query transaction database. With given minimum support (min_sup) and minimum share support (min_share_sup), each SFP includes a core frequent pattern (BFP) used to draw other frequent or sub-frequent items. A latter query returns a subset of a SFP as the result. To realize the SFPs mining, this paper proposes the structure of SFP-tree along with relative mining algorithms. The main contribution includes: (1) Describes the concept of Supplement Frequent Pattern; (2) Proposes the SFP-tree along with frequency-Ascending order header table FP-Tree (AFP-Tree) and Conditional Mix Pattern Tree (CMP-Tree); (3) Proposes the SFPs mining algorithms based on SFP-Tree; and (4) Conducts the performance experiment on both synthetic and real datasets. The result shows the effectiveness and efficiency of the SFPs mining algorithm based on SFP-Tree.
This work is supported by the National Natural Science Foundation of China under Grant No. 60773169 and No. 60702075, Development Foundation of Chengdu University of Information Technology(KYTZ200811).
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Liu, Y., Liu, Y., Zeng, T., Xu, K., Tang, R. (2008). Mining Supplemental Frequent Patterns. In: Tang, C., Ling, C.X., Zhou, X., Cercone, N.J., Li, X. (eds) Advanced Data Mining and Applications. ADMA 2008. Lecture Notes in Computer Science(), vol 5139. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88192-6_16
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