Computing the Mixed Concept Lattice

Pérez-Gámez, Francisco; Enciso, Manuel; López-Rodríguez, Domingo; Mora, Ángel

doi:10.1007/978-3-031-08971-8_8

Cited by 1 publication

(1 citation statement)

References 13 publications

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“…a user may want to search a component with provided services, and consider in a second step the required services, that other components could provide. Another potential use of the DP Separate/Gather Views could be to consider positive versus negative description of objects, a question that has been addressed in [30], to complete their approach using an additional point of view.…”

Section: Perspectivesmentioning

confidence: 99%

Relational Concept Analysis in Practice: Capitalizing on Data Modeling Using Design Patterns

Braud

Dolques

Huchard

et al. 2023

Formal Concept Analysis

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Many applications of Formal Concept Analysis (FCA) and its diverse extensions have been carried out in recent years. Among these extensions, Relational Concept Analysis (RCA) is one approach for addressing knowledge discovery in multi-relational datasets. Applying RCA requires stating a question of interest and encoding the dataset into the input RCA data model, i.e. an Entity-Relationship model with only Boolean attributes in the entity description and unidirectional binary relationships. From the various concrete RCA applications, recurring encoding patterns can be observed, that we aim to capitalize taking software engineering design patterns as a source of inspiration. This capitalization work intends to rationalize and facilitate encoding in future RCA applications. In this paper, we describe an approach for defining such design patterns, and we present two design patterns: "Separate/Gather Views" and "Level Relations".

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Section: Perspectivesmentioning

confidence: 99%