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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.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Cuzzocrea, A. (2007). MRE-KDD+: A MULTI-RESOLUTION, ENSEMBLE-BASED MODEL FOR ADVANCED KNOLWEDGE DISCOVERY. In Proceedings of the Ninth International Conference on Enterprise Information Systems - Volume 1: ICEIS; ISBN 978-972-8865-89-4; ISSN 2184-4992, SciTePress, pages 152-158. DOI: 10.5220/0002404001520158

@conference{iceis07,
author={Alfredo Cuzzocrea.},
title={MRE-KDD+: A MULTI-RESOLUTION, ENSEMBLE-BASED MODEL FOR ADVANCED KNOLWEDGE DISCOVERY},
booktitle={Proceedings of the Ninth International Conference on Enterprise Information Systems - Volume 1: ICEIS},
year={2007},
pages={152-158},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002404001520158},
isbn={978-972-8865-89-4},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the Ninth International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - MRE-KDD+: A MULTI-RESOLUTION, ENSEMBLE-BASED MODEL FOR ADVANCED KNOLWEDGE DISCOVERY
SN - 978-972-8865-89-4
IS - 2184-4992
AU - Cuzzocrea, A.
PY - 2007
SP - 152
EP - 158
DO - 10.5220/0002404001520158
PB - SciTePress