Frequent-Itemset Mining Using Locality-Sensitive Hashing
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[1] Heikki Mannila,et al. Discovery of Frequent Episodes in Event Sequences , 1997, Data Mining and Knowledge Discovery.
[2] Piotr Indyk,et al. Approximate nearest neighbors: towards removing the curse of dimensionality , 1998, STOC '98.
[3] H. Mannila,et al. Discovering all most specific sentences , 2003, TODS.
[4] Piotr Indyk,et al. Similarity Search in High Dimensions via Hashing , 1999, VLDB.
[5] Alan M. Frieze,et al. Min-Wise Independent Permutations , 2000, J. Comput. Syst. Sci..
[6] Ramakrishnan Srikant,et al. Fast Algorithms for Mining Association Rules in Large Databases , 1994, VLDB.
[7] Tomasz Imielinski,et al. Mining association rules between sets of items in large databases , 1993, SIGMOD Conference.
[8] Edith Cohen,et al. Finding interesting associations without support pruning , 2000, Proceedings of 16th International Conference on Data Engineering (Cat. No.00CB37073).
[9] Philip S. Yu,et al. Clustering by pattern similarity in large data sets , 2002, SIGMOD '02.
[10] Rajeev Motwani,et al. Beyond Market Baskets: Generalizing Association Rules to Dependence Rules , 1998, Data Mining and Knowledge Discovery.
[11] Ping Li,et al. Asymmetric Minwise Hashing for Indexing Binary Inner Products and Set Containment , 2015, WWW.
[12] Philip S. Yu,et al. An effective hash-based algorithm for mining association rules , 1995, SIGMOD '95.
[13] Rasmus Pagh. Locality-sensitive Hashing without False Negatives , 2016, SODA.