In this paper, we develop a connection between association queries and formal concept analysis. An association query discovers dependencies among values of an attribute grouped by other, non-primary attributes in a given relation. Formal concept analysis deals with formal mathematical tools and techniques to develop and analyze relationship between concepts and to develop concept structures. We show that dependencies found by an association query can be derived from a concept structure. Keywords- Association queries, formal concept analysis, dependency relations, concept structures. 1 Introduction An association query discovers dependencies among values of an attribute grouped by some other attributes in a given relation. A specific case ...
Abstract. Symbolic objects were originally intended to bring both more structure in data and more in...
International audienceSymbolic objects were originally intended to bring both more structure in data...
International audienceEfficiently discovering causal relations from data and representing them in a ...
An association rule discovers dependencies among values of an attribute grouped by some other attrib...
In this study we utilize formal concept analysis to model association rules. Formal concept analysis...
Abstract. Association rules are a popular knowledge discovery tech-nique for warehouse basket analys...
The flood of data has led to new techniques with the ability to assist humans intelligently and auto...
In this paper we describe a formal framework for the problem of mining association rules. The theore...
Formal concept analysis (FCA) has been a topic of interest for many researches since its introductio...
Colloque avec actes et comité de lecture. internationale.International audienceAssociation rules are...
International audienceKnowledge discovery in large and complex datasets is one of the main topics ad...
Formal Concept Analysis (FCA) has been successfully ap- plied to data in a number of problem domain...
Concepts are often related to short sequences of words that occur frequently together across the tex...
International audienceThe processing of complex data is admittedly among the major concerns of knowl...
Association rule mining (ARM) is the task of identifying meaningful implication rules exhibited in a...
Abstract. Symbolic objects were originally intended to bring both more structure in data and more in...
International audienceSymbolic objects were originally intended to bring both more structure in data...
International audienceEfficiently discovering causal relations from data and representing them in a ...
An association rule discovers dependencies among values of an attribute grouped by some other attrib...
In this study we utilize formal concept analysis to model association rules. Formal concept analysis...
Abstract. Association rules are a popular knowledge discovery tech-nique for warehouse basket analys...
The flood of data has led to new techniques with the ability to assist humans intelligently and auto...
In this paper we describe a formal framework for the problem of mining association rules. The theore...
Formal concept analysis (FCA) has been a topic of interest for many researches since its introductio...
Colloque avec actes et comité de lecture. internationale.International audienceAssociation rules are...
International audienceKnowledge discovery in large and complex datasets is one of the main topics ad...
Formal Concept Analysis (FCA) has been successfully ap- plied to data in a number of problem domain...
Concepts are often related to short sequences of words that occur frequently together across the tex...
International audienceThe processing of complex data is admittedly among the major concerns of knowl...
Association rule mining (ARM) is the task of identifying meaningful implication rules exhibited in a...
Abstract. Symbolic objects were originally intended to bring both more structure in data and more in...
International audienceSymbolic objects were originally intended to bring both more structure in data...
International audienceEfficiently discovering causal relations from data and representing them in a ...