Published 2007
| Version v1
Book section
Knowledge extraction using a conceptual information system (ExCIS)
- Creators
- Brisson, Laurent
- Others:
- Laboratoire d'Informatique, Signaux, et Systèmes de Sophia Antipolis (I3S) ; Université Nice Sophia Antipolis (1965 - 2019) (UNS) ; COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)
- Lecture notes in computer science (LNCS)
Description
It is a well known fact that the data mining process can generate thousands of patterns from data. Various measures exist for evaluating and ranking these discovered patterns but often they dont consider user subjective interest. We propose an ontology-based data-mining methodology called ExCIS (Extraction using a Conceptual Information System) for integrating expert prior knowledge in a data-mining process. Its originality is to build a specific Conceptual Information System related to the application domain in order to improve datasets preparation and results interpretation. This paper focus on our ontological choices and an interestingness measure IMAK which evaluates patterns considering expert knowledge.
Abstract
International audience
Additional details
- URL
- https://hal.archives-ouvertes.fr/hal-02281800
- URN
- urn:oai:HAL:hal-02281800v1
- Origin repository
- UNICA