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Found 14 papers, 0 papers with code
Formal concept analysis for evaluating intrinsic dimension of a natural language
Some results of a computational experiment for determining the intrinsic dimension of linguistic varieties for the Bengali and Russian languages are presented.
Delta-Closure Structure for Studying Data Distribution
In this paper, we revisit pattern mining and study the distribution underlying a binary dataset thanks to the closure structure which is based on passkeys, i. e., minimum generators in equivalence classes robust to noise.
Decision Concept Lattice vs. Decision Trees and Random Forests
Decision trees and their ensembles are very popular models of supervised machine learning.
Mint: MDL-based approach for Mining INTeresting Numerical Pattern Sets
Pattern mining is well established in data mining research, especially for mining binary datasets.
Discovery data topology with the closure structure. Theoretical and practical aspects
The closure structure allows one to understand the topology of the dataset in the whole and the inherent complexity of the data.
Ordered Sets for Data Analysis
On the one hand, data often have a complex structure with natural order on it.
Mining Best Closed Itemsets for Projection-antimonotonic Constraints in Polynomial Time
One of the first constraints proposed in pattern mining is support (frequency) of a pattern in a dataset.
On interestingness measures of formal concepts
Formal concepts and closed itemsets proved to be of big importance for knowledge discovery, both as a tool for concise representation of association rules and a tool for clustering and constructing domain taxonomies and ontologies.
Fast Generation of Best Interval Patterns for Nonmonotonic Constraints
In this paper we consider stability and $\Delta$-measure, which are nonmonotonic constraints, and apply them to interval tuple datasets.
Graphlet-based lazy associative graph classification
The paper addresses the graph classification problem and introduces a modification of the lazy associative classification method to efficiently handle intersections of graphs.
On mining complex sequential data by means of FCA and pattern structures
Pattern structures are used for mining complex data (such as sequences or graphs) and are based on a subsumption operation, which in our case is defined with respect to the partial order on sequences.
Interactive Error Correction in Implicative Theories
First, two classes of errors that may affect implicative theories are singled out.
Concept Stability for Constructing Taxonomies of Web-site Users
Owners of a web-site are often interested in analysis of groups of users of their site.
