Author:
Alfredo Cuzzocrea
Affiliation:
University of Calabria, Italy
Keyword(s):
On-Line Analytical Processing, Data Mining, On-Line Analytical Mining, Knowledge Discovery from Large Databases and Data Warehouses, Cooperative Information Systems.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Business Analytics
;
Data Engineering
;
Data Mining
;
Data Warehouses and OLAP
;
Databases and Information Systems Integration
;
Datamining
;
Enterprise Information Systems
;
Health Information Systems
;
Sensor Networks
;
Signal Processing
;
Soft Computing
Abstract:
In data-intensive scenarios, data repositories expose very different formats, and knowledge representation schemes are very heterogeneous accordingly. As a consequence, a relevant research challenge is how to efficiently integrate, process and mine such distributed knowledge in order to make available it to end-users/applications in an integrated and summarized manner. Starting from these considerations, in this paper we propose an OLAM-based model for advanced knowledge discovery, called Multi-Resolution Ensemble-based Model for Advanced Knowledge Discovery in Large Databases and Data Warehouses (MRE-KDD+). MRE-KDD+ integrates in a meaningfully manner several theoretical amenities coming from On-Line Analytical Processing (OLAP), Data Mining (DM) and Knowledge Discovery in Databases (KDD), and results to be an effective model for supporting advanced decision-support processes in many fields of real-life data-intensive applications.