Measurement, selection, and visualization of association rules: A compositional data perspective: A Compositional Data perspective on Association Rules

Association rule mining is a powerful data analytic technique used for extracting information from transaction databases with a collection of itemsets. The aim is to indicate what item goes with what item (ie, an association rule) in a set of collected transactions. It is extensively used in text an...

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Detalles Bibliográficos
Autores: Vives Mestres, Marina, Kenett, Ron S., Thió i Fernández de Henestrosa, Santiago, Martín Fernández, Josep Antoni
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2022
País:España
Institución:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:10256/19751
Acceso en línea:http://hdl.handle.net/10256/19751
Access Level:acceso abierto
Palabra clave:Mineria de regles d’associació
Association rule mining
Mineria de dades
Data mining
Descripción
Sumario:Association rule mining is a powerful data analytic technique used for extracting information from transaction databases with a collection of itemsets. The aim is to indicate what item goes with what item (ie, an association rule) in a set of collected transactions. It is extensively used in text analytics of text records or social media. Here we use Compositional Data analysis (CoDa) techniques to generate new visualizations and insights from association rule mining. These CoDa methods show the relationship between itemsets, their strength, and direction of dependency. Moreover, after expressing each association rule as a contingency table, we discuss two statistical tests to guide identification of the relevant rules by analyzing the relative importance of the elements of the table. As an example, we use these visualizations and statistical tests for investigating the association of negative mood emotions to various types of headache/migraine events. Data for those analysis comes from N1-HeadacheTM, a digital platform where individual users record attacks and symptoms as well as their daily exposure to a list of potential factors