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InClose, a Fast Algorithm for Computing Formal Concepts
 the Seventeenth International Conference on Conceptual Structures
, 2009
"... Abstract. This paper presents an algorithm, called InClose, that uses incremental closure and matrix searching to quickly compute all formal concepts in a formal context. InClose is based, conceptually, on a well known algorithm called CloseByOne. The serial version of a recently published algor ..."
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Abstract. This paper presents an algorithm, called InClose, that uses incremental closure and matrix searching to quickly compute all formal concepts in a formal context. InClose is based, conceptually, on a well known algorithm called CloseByOne. The serial version of a recently published algorithm (Krajca, 2008) was shown to be in the order of 100 times faster than several wellknown algorithms, and timings of other algorithms in reviews suggest that none of them are faster than Krajca. This paper compares InClose to Krajca, discussing computational methods, data requirements and memory considerations. From experiments using several public data sets and random data, this paper shows that InClose is in the order of 20 times faster than Krajca. InClose is small, straightforward, requires no matrix preprocessing and is simple to implement. 1
Knowledge Discovery through creating Formal Contexts
"... This document is the author deposited version. You are advised to consult the publisher's version if you wish to cite from it. ..."
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Cited by 4 (4 self)
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This document is the author deposited version. You are advised to consult the publisher's version if you wish to cite from it.
Mining Constrained CrossGraph Cliques in Dynamic Networks
"... have been recently proposed to mine closed patterns in ternary relations, i.e., a generalization of the socalled formal concept extraction from binary relations. In this paper, we consider the specific context where a ternary relation denotes the value of a graph adjacency matrix (i. e., a Vertices ..."
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Cited by 3 (2 self)
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have been recently proposed to mine closed patterns in ternary relations, i.e., a generalization of the socalled formal concept extraction from binary relations. In this paper, we consider the specific context where a ternary relation denotes the value of a graph adjacency matrix (i. e., a Vertices × Vertices matrix) at different timestamps. We discuss the constraintbased extraction of patterns in such dynamic graphs. We formalize the concept of δcontiguous closed 3clique and we discuss the availability of a complete algorithm for mining them. It is based on a specialization of the enumeration strategy implemented in DataPeeler. Indeed, the relevant cliques are specified by means of a conjunction of constraints which can be efficiently exploited. The addedvalue of our strategy for computing constrained clique patterns is assessed on a real dataset about a public bicycle renting system. The raw data encode the relationships between the renting stations during one year. The extracted δcontiguous closed 3cliques are shown to be consistent with our knowledge on the considered city.
Knowledge Discovery through Creating Formal Contexts
"... This document is the author deposited version. You are advised to consult the publisher's version if you wish to cite from it. ..."
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This document is the author deposited version. You are advised to consult the publisher's version if you wish to cite from it.
New Applications of Formal Concept Analysis: A Need for Original Pattern Domains
"... Abstract. We survey the results obtained by our research group (joint ..."
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Tackling Closed Pattern Relevancy In nary Relations
"... Abstract. For the last decade, set pattern discovery from binary relations has been studied in depth. Today, many complete and efficient algorithms for frequent closed set mining are available. More recently, their extensions towards nary relation mining have been considered. In this paper, we cons ..."
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Abstract. For the last decade, set pattern discovery from binary relations has been studied in depth. Today, many complete and efficient algorithms for frequent closed set mining are available. More recently, their extensions towards nary relation mining have been considered. In this paper, we consider the recent proposal for closed nset pattern discovery and we discuss their relevancy. Indeed, starting with experiments on two reallife multidimensional data sets, we discuss the quality of the extracted local patterns thanks to an inside and outside perspective on the discovered closed nsets. This original analysis enables to support the declarative specification of a priori relevant patterns thanks to the conjunction of primitive constraints (minimal size, minimal area, δisolated and faulttolerance constraints) they have to satisfy. Interestingly, some of these primitive constraints can be exploited within available solvers. 1
http://shura.shu.ac.uk InClose, a Fast Algorithm for Computing Formal Concepts
"... This document is the author deposited version. You are advised to consult the publisher's version if you wish to cite from it. Published version ANDREWS, S. (2009). InClose, a fast algorithm for computing formal concepts. In: ..."
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This document is the author deposited version. You are advised to consult the publisher's version if you wish to cite from it. Published version ANDREWS, S. (2009). InClose, a fast algorithm for computing formal concepts. In: