Authors:
Filipe Mota Pinto
1
;
Alzira Marques
1
and
Manuel Filipe Santos
2
Affiliations:
1
Instituto Politécnico de Leiria, Portugal
;
2
Escola de Engenharia, Universidade do Minho, Portugal
Keyword(s):
Ontologies, Database Marketing, Knowledge Extraction Process, Action Research.
Related
Ontology
Subjects/Areas/Topics:
Agents
;
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Biomedical Engineering
;
Computer-Supported Education
;
Data Engineering
;
e-Learning
;
Enterprise Information Systems
;
Health Information Systems
;
Informatics in Control, Automation and Robotics
;
Information Systems Analysis and Specification
;
Information Technologies Supporting Learning
;
Intelligent Agents
;
Intelligent Control Systems and Optimization
;
Intelligent Tutoring Systems
;
Internet Technology
;
Knowledge Engineering
;
Knowledge Engineering and Ontology Development
;
Knowledge Management
;
Knowledge-Based Systems
;
Knowledge-Based Systems Applications
;
Ontologies and the Semantic Web
;
Ontology Engineering
;
Society, e-Business and e-Government
;
Software Engineering
;
Symbolic Systems
;
Web Information Systems and Technologies
Abstract:
This work proposes an ontology based system architecture which works as developer guide to a database marketing practitioner. Actually marketing departments handles daily with a great volume of data which are normally task or marketing activity dependent. This sometimes requires specific knowledge background and framework. This article aims to introduce an unexplored research at Database Marketing: the ontological approach to the Database Marketing process. Here we propose a generic framework supported by ontologies and knowledge extraction from databases techniques. Therefore this paper has two purposes: to integrate ontological approach in Database Marketing and to create domain ontology with a knowledge base that will enhance the entire process at both levels: marketing and knowledge extraction techniques. Our work is based in the Action Research methodology. At the end of this research we present some experiments in order to illustrate how knowledge base works and how can it be u
seful to user.
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