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- research-articleDecember 2022
A Machine Learning Method to Reveal Closed Sets of Common Features of Objects Using Constraint Programming
Automation and Remote Control (ARCO), Volume 83, Issue 12Pages 1995–2005https://doi.org/10.1134/S00051179220120116AbstractTo solve machine learning problems, we have developed a method to identify closed sets of common features of objects (patterns) of the training sample. The novelty of the method lies in the fact that it is implemented within the concept of ...
- ArticleDecember 2013
Pattern-Based Topic Models for Information Filtering
ICDMW '13: Proceedings of the 2013 IEEE 13th International Conference on Data Mining WorkshopsPages 921–928https://doi.org/10.1109/ICDMW.2013.30Topic modelling, such as Latent Dirichlet Allocation (LDA), was proposed to generate statistical models to represent multiple topics in a collection of documents, which has been widely utilized in the fields of machine learning and information retrieval, ...
- research-articleJuly 2010
Authorship classification: a syntactic tree mining approach
UP '10: Proceedings of the ACM SIGKDD Workshop on Useful PatternsPages 65–73https://doi.org/10.1145/1816112.1816121In the past, there have been dozens of studies on automatic authorship classification, and many of these studies concluded that the writing style is one of the best indicators of original authorship. From among the hundreds of features which were ...
- ArticleAugust 2009
Closed Non Derivable Data Cubes Based on Non Derivable Minimal Generators
ADMA '09: Proceedings of the 5th International Conference on Advanced Data Mining and ApplicationsPages 55–66https://doi.org/10.1007/978-3-642-03348-3_9It is well recognized that data cubes often produce huge outputs. Several efforts were devoted to this problem through closed cubes, where cells preserving aggregation semantics are losslessly reduced to one cell. In this paper, we introduce the concept ...
- ArticleAugust 2005
Mining closed relational graphs with connectivity constraints
KDD '05: Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data miningPages 324–333https://doi.org/10.1145/1081870.1081908Relational graphs are widely used in modeling large scale networks such as biological networks and social networks. In this kind of graph, connectivity becomes critical in identifying highly associated groups and clusters. In this paper, we investigate ...
- ArticleAugust 2004
Efficient closed pattern mining in the presence of tough block constraints
KDD '04: Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data miningPages 138–147https://doi.org/10.1145/1014052.1014070Various constrained frequent pattern mining problem formulations and associated algorithms have been developed that enable the user to specify various itemset-based constraints that better capture the underlying application requirements and ...
- ArticleAugust 2003
Carpenter: finding closed patterns in long biological datasets
KDD '03: Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data miningPages 637–642https://doi.org/10.1145/956750.956832The growth of bioinformatics has resulted in datasets with new characteristics. These datasets typically contain a large number of columns and a small number of rows. For example, many gene expression datasets may contain 10,000-100,000 columns but only ...
- ArticleAugust 2003
CloseGraph: mining closed frequent graph patterns
KDD '03: Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data miningPages 286–295https://doi.org/10.1145/956750.956784Recent research on pattern discovery has progressed form mining frequent itemsets and sequences to mining structured patterns including trees, lattices, and graphs. As a general data structure, graph can model complicated relations among data with wide ...