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Reducing borders of k-disjunction free representations of frequent patterns.. SAC, стр. 559-563. ACM, (2004)Unsupervised Anomaly Detection in Stream Data with Online Evolving Spiking Neural Networks., , , , и . CoRR, (2019)Efficient Search of Cosine and Tanimoto Near Duplicates among Vectors with Domains Consisting of Zero, a Positive Number and a Negative Number., и . IEA/AIE (2), том 8482 из Lecture Notes in Computer Science, стр. 160-170. Springer, (2014)A Neighborhood-Based Clustering by Means of the Triangle Inequality., и . IDEAL, том 6283 из Lecture Notes in Computer Science, стр. 284-291. Springer, (2010)Inducing Theory for the Rule Set.. Rough Sets and Current Trends in Computing, том 2005 из Lecture Notes in Computer Science, стр. 391-398. Springer, (2000)Association Rules in Incomplete Databases.. PAKDD, том 1574 из Lecture Notes in Computer Science, стр. 84-93. Springer, (1999)Concise Representation of Frequent Patterns Based on Generalized Disjunction-Free Generators., и . PAKDD, том 2336 из Lecture Notes in Computer Science, стр. 159-171. Springer, (2002)Air pollution prediction with clustering-based ensemble of evolving spiking neural networks and a case study for London area., , , и . Environ. Model. Softw., (2019)A Lossless Representation for Association Rules Satisfying Multiple Evaluation Criteria.. ACIIDS (2), том 9622 из Lecture Notes in Computer Science, стр. 147-158. Springer, (2016)Legitimate Approach to Association Rules under Incompleteness., и . ISMIS, том 1932 из Lecture Notes in Computer Science, стр. 505-514. Springer, (2000)