Abstract
In mining constraint frequent neighboring class set, it has been reported that the present algorithm is unsuitable for mining long constraint frequent neighboring class set in spatial database. This paper proposes a filling algorithm of mining constraint frequent neighboring class set, which is suitable for mining any length constraint frequent neighboring class set. In order to improve efficiency of mining algorithm, the algorithm uses computing subset of neighboring class set to generate candidate via top-down strategy. Meanwhile, it uses the method of filling subset to double generate candidate frequent neighboring class set, and it also uses ‘and’ operation of corresponding integer to compute support. The result of experiment indicates that the algorithm is faster and more efficient than other algorithms when mining constraint frequent neighboring class sets.
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References
Ma, R., Pu, Y.X., Ma, X.D.: GIS Spatial Association Pattern Ming. Science Press, Beijing (2007)
Ma, R., He, Z.-Y.: Mining Complete and Correct Frequent Neighboring Class Sets from Spatial Databases. Geomatics and Information Science of Wuhan University 32(2), 112–114 (2007)
Fang, G.: An Algorithm of Alternately Mining Frequent Neighboring Class Set. In: Tan, Y., Shi, Y., Tan, K.C. (eds.) ICSI 2010, Part II. LNCS, vol. 6146, pp. 588–593. Springer, Heidelberg (2010)
Zhang, X., Su, F.-Z., Shi, Y.-S., Zhang, D.: Research on Progress of Spatial Association Rule Mining. Progress in Geograph 26(6), 119–128 (2007)
Fang, G., Wei, Z., Yin, Q.: An Algorithm of Constrained Spatial Association Rules Based on Binary. In: Sun, F., Zhang, J., Tan, Y., Cao, J., Yu, W. (eds.) ISNN 2008,, Part II. LNCS, vol. 5264, pp. 21–29. Springer, Heidelberg (2008)
Fang, G., Wei, Z., Yin, Q.: Extraction of Spatial Association Rules Based on Binary Mining Algorithm in Mobile Computing. In: IEEE Information Conference on Information and Automation, pp. 1571–1575. IEEE Press (2008)
Liu, Y.-L., Fang, G.: The research and application of a transaction complement mining algorithm. Journal of Computer Engineering and Applications 44(35), 168–170 (2008)
Fang, G., Liu, Y.-L.: Application of Binary System-Based Spatial Mining Algorithm in Mobile Intelligent Systems. Journal of Southwest University (Natural Science Edition) 31(1), 95–99 (2009)
Fang, G., Xiong, J., Du, X.-L., Tang, X.-B.: Frequent neighboring class set mining. In: 2010 7th International Conference on Fuzzy Systems and Knowledge Discovery, pp. 1442–1445 (2010)
Tu, C.-S., Fang, G.: A double search mining algorithm in frequent neighboring class set. In: 2010 IEEE International Conference on Intelligent Computing and Intelligent Systems, pp. 417–420 (2010)
Fang, G., Xiong, J., Chen, X.: Frequent Neighboring Class Set Mining with Constraint Condition. In: International Conference on Progress in Informatics and Computing, pp. 242–245 (2010)
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Hu, L., Li, Y., Xiong, J., Fang, G. (2012). A Filling Algorithm of Mining Constraint Frequent Neighboring Class Set. In: Liu, C., Wang, L., Yang, A. (eds) Information Computing and Applications. ICICA 2012. Communications in Computer and Information Science, vol 307. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34038-3_25
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DOI: https://doi.org/10.1007/978-3-642-34038-3_25
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-34037-6
Online ISBN: 978-3-642-34038-3
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