Title :
aK-Mode: New algorithm to cluster OLAP requirement schemas
Author :
Arfaoui, Nouha ; Akaichi, Jalel
Author_Institution :
BIRT- Inst. Super. de Gestion, Le Bardo, Tunisia
Abstract :
Different methods are proposed to generate the schema of data mart. We propose a new one that starts by clustering the OLAP requirements that are represented as schemas, then, it generates the schemas of the data mart one for each cluster, and finally it validates them. In this work, we will focus on the first step and we will propose a new algorithm “aK-Mode” to cluster our schemas. Indeed, many techniques exist, they are applied to numerical and categorical data, but they cannot be used in our case since we have to take into consideration the semantic aspect while making the comparison. The new algorithm extends the k-mode by modifying the dissimilarity measure.
Keywords :
data mining; data warehouses; pattern clustering; OLAP requirement schema clustering; aK-Mode algorithm; categorical data; data mart; dissimilarity measure; numerical data; schema generation; Algorithm design and analysis; Association rules; Clustering algorithms; Databases; Prediction algorithms; Semantics; Clustering; Data Mart Schema; OLAP Requirement schema; Simple Matching; ak-mode;
Conference_Titel :
Control, Decision and Information Technologies (CoDIT), 2013 International Conference on
Conference_Location :
Hammamet
Print_ISBN :
978-1-4673-5547-6
DOI :
10.1109/CoDIT.2013.6689557