Abstract
The class of closed patterns is a well known condensed representations of frequent patterns, and have recently attracted considerable interest. In this paper, we propose an efficient algorithm LCM (Linear time Closed pattern Miner) for mining frequent closed patterns from large transaction databases. The main theoretical contribution is our proposed prefix-preserving closure extension of closed patterns, which enables us to search all frequent closed patterns in a depth-first manner, in linear time for the number of frequent closed patterns. Our algorithm do not need any storage space for the previously obtained patterns, while the existing algorithms needs it. Performance comparisons of LCM with straightforward algorithms demonstrate the advantages of our prefix-preserving closure extension.
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References
Agrawal, R., Mannila, H., Srikant, R., Toivonen, H., Verkamo, A.I.: Fast Discovery of Association Rules. In: Advances in Knowledge Discovery and Data Mining, pp. 307–328. MIT Press, Cambridge (1996)
Asai, T., Abe, K., Kawasoe, S., Arimura, H., Sakamoto, H., Arikawa, S.: Efficient Substructure Discovery from Large Semi-structured Data. In: Proc. SDM 2002, SIAM, Philadelphia (2002)
Asai, T., Arimura, H., Abe, K., Kawasoe, S., Arikawa, S.: Online Algorithms for Mining Semistructured Data Stream. In: Proc. IEEE ICDM 2002, pp. 27–34 (2002)
Asai, T., Arimura, H., Uno, T., Nakano, S.: Discovering Frequent Substructures in Large Unordered Trees. In: Grieser, G., Tanaka, Y., Yamamoto, A. (eds.) DS 2003. LNCS (LNAI), vol. 2843, pp. 47–61. Springer, Heidelberg (2003)
Bayardo Jr., R.J.: Efficiently Mining Long Patterns from Databases. In: Proc. SIGMOD 1998, pp. 85–93 (1998)
Bastide, Y., Taouil, R., Pasquier, N., Stumme, G., Lakhal, L.: Mining Frequent Patterns with Counting Inference. SIGKDD Explr. 2(2), 66–75 (2000)
Goethals, B.: The FIMI 2003 Homepage (2003), http://fimi.cs.helsinki.fi/
Boros, E., Gurvich, V., Khachiyan, L., Makino, K.: On the Complexity of Generating Maximal Frequent and Minimal Infrequent Sets. In: Alt, H., Ferreira, A. (eds.) STACS 2002. LNCS, vol. 2285, pp. 133–141. Springer, Heidelberg (2002)
Burdick, D., Calimlim, M., Gehrke, J.: MAFIA: A Maximal Frequent Itemset Algorithm for Transactional Databases. In: Proc. ICDE 2001, pp. 443–452 (2001)
Han, J., Pei, J., Yin, Y.: Mining Frequent Patterns without Candidate Generation. In: Proc. SIGMOD 2000, pp. 1–12 (2000)
Kohavi, R., Brodley, C.E., Frasca, B., Mason, L., Zheng, Z.: KDD-Cup 2000 Organizers’ Report: Peeling the Onion. SIGKDD Explr. 2(2), 86–98 (2000)
Mannila, H., Toivonen, H.: Multiple Uses of Frequent Sets and Condensed Representations. In: Proc. KDD 1996, pp. 189–194 (1996)
Pasquier, N., Bastide, Y., Taouil, R., Lakhal, L.: Efficient Mining of Association Rules Using Closed Itemset Lattices. Inform. Syst. 24(1), 25–46 (1999)
Pasquier, N., Bastide, Y., Taouil, R., Lakhal, L.: Discovering Frequent Closed Itemsets for Association Rules. In: Beeri, C., Bruneman, P. (eds.) ICDT 1999. LNCS, vol. 1540, pp. 398–416. Springer, Heidelberg (1998)
Pei, J., Han, J., Mao, R.: CLOSET: An Efficient Algorithm for Mining Frequent Closed Itemsets. In: Proc. DMKD 2000, pp. 21–30 (2000)
Rymon, R.: Search Through Systematic Set Enumeration. In: Proc. KR 1992, pp. 268–275 (1992)
Tzvetkov, P., Yan, X., Han, J.: TSP: Mining Top-K Closed Sequential Patterns. In: Proc. ICDM 2003 (2003)
Uno, T., Asai, T., Uchida, Y., Arimura, H.: LCM: An Efficient Algorithm for Enumerating Frequent Closed Item Sets. In: Proc. IEEE ICDM 2003 Workshop FIMI 2003 (2003) (Available as CEUR Workshop Proc. series, vol. 90, http://ceur-ws.org/vol-90 )
Yan, X., Han, J.: CloseGraph: Mining Closed Frequent Graph Patterns. In: Proc. KDD 2003, ACM Press, New York (2003)
Zaki, M.J.: Scalable Algorithms for Association Mining. Knowledge and Data Engineering 12(2), 372–390 (2000)
Zaki, M.J., Hsiao, C.: CHARM: An Efficient Algorithm for Closed Itemset Mining. In: Proc. SDM 2002, pp. 457–473. SIAM, Philadelphia (2002)
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Uno, T., Asai, T., Uchida, Y., Arimura, H. (2004). An Efficient Algorithm for Enumerating Closed Patterns in Transaction Databases. In: Suzuki, E., Arikawa, S. (eds) Discovery Science. DS 2004. Lecture Notes in Computer Science(), vol 3245. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30214-8_2
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DOI: https://doi.org/10.1007/978-3-540-30214-8_2
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