Results 51 to 60 of about 73 (69)
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2017
This book provides a gentle introduction to redescription mining, a versatile data mining tool that is useful to find distinct common characterizations of the same objects and, vice versa, to identify sets of objects that admit multiple shared descriptions.
Galbrun, Esther, Miettinen, Pauli
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This book provides a gentle introduction to redescription mining, a versatile data mining tool that is useful to find distinct common characterizations of the same objects and, vice versa, to identify sets of objects that admit multiple shared descriptions.
Galbrun, Esther, Miettinen, Pauli
openaire +2 more sources
Reasoning about sets using redescription mining
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining, 2005Redescription mining is a newly introduced data mining problem that seeks to find subsets of data that afford multiple definitions. It can be viewed as a generalization of association rule mining, from finding implications to equivalences; as a form of conceptual clustering, where the goal is to identify clusters that afford dual characterizations; and
Mohammed J. Zaki, Naren Ramakrishnan
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Algorithms for Redescription Mining
2017The aim of redescription mining is to find valid redescriptions for given data, query language, similarity relation, and user-specified constraints. In other words, we need to explore the search space consisting of query pairs from the query language, looking for those pairs that have similar enough support in the data and that satisfy the other ...
Esther Galbrun, Pauli Miettinen
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2017
In scientific investigations, data oftentimes differ in nature; for instance, they might originate from distinct sources or be cast over separate terminologies. In order to gain insight into the phenomenon of interest, an intuitive first task is to identify the correspondences that exist between these different aspects. This is the motivating principle
Esther Galbrun, Pauli Miettinen
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In scientific investigations, data oftentimes differ in nature; for instance, they might originate from distinct sources or be cast over separate terminologies. In order to gain insight into the phenomenon of interest, an intuitive first task is to identify the correspondences that exist between these different aspects. This is the motivating principle
Esther Galbrun, Pauli Miettinen
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Extending Redescription Mining to Multiple Views
2018Redescription mining is a data mining task that discovers re-descriptions of different subsets of entities from available data. Locating such re-descriptions is important in many scientific disciplines because it allows detecting different types of associations including synergy of different attributes of interest. There exist a number of redescription
Mihelčić, Matej +2 more
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Interpreter of Maladies: Redescription Mining Applied to Biomedical Data Analysis
Pharmacogenomics, 2006Comprehensive, systematic and integrated data-centric statistical approaches to disease modeling can provide powerful frameworks for understanding disease etiology. Here, one such computational framework based on redescription mining in both its incarnations, static and dynamic, is discussed. The static framework provides bioinformatic tools applicable
Peter, Waltman +2 more
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Mining Non-redundant Rules for Redescription Datasets Based on FCA
2010 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, 2010The notions and algorithms of generating basis for exactness rules and the proper basis for conditional rules of redescription database are presented using closure operator of Galois connection based on the operations of formal concept analysis (FCA). It is demonstrated that constructed rules of redescription database are minimal non-redundant.
Yuanyuan Wei, Min Wei
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Redescription Mining with Multi-target Predictive Clustering Trees
2016Redescription mining is a field of knowledge discovery that aims to find different descriptions of subsets of elements in the data by using two or more disjoint sets of descriptive attributes. The ability to find connections between different sets of descriptive attributes and provide a more comprehensive set of rules makes it very useful in practice ...
Mihelčić, Matej +3 more
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Applications, Variants, and Extensions of Redescription Mining
2017Redescription mining is a data analysis task that aims at finding distinct common characterizations of the same objects. After defining the core problem and presenting algorithmic techniques to solve this task, we look in this chapter at some of the applications, variants, and extensions of redescription mining.
Esther Galbrun, Pauli Miettinen
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Redescription mining augmented with random forest of multi-target predictive clustering trees
Journal of Intelligent Information Systems, 2017In this work, we present a redescription mining algorithm that uses Random Forest of Predictive Clustering Trees (RFPCTs) for generating and iteratively improving a set of redescriptions. The approach uses information about element membership in different queries, generated from a single constructed PCT, to explore redescription space, while queries ...
Mihelčić, Matej +3 more
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