Knowledge discovery from data is a process that aims to extract potentially useful knowledge hidden in large databases. Current works, in order to evaluate extracted patterns use interestingness measures. Such measures of interestingness are divided into objective measures that depend only on the structure of a pattern and the underlying data...
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December 13, 2006 (v1)PublicationUploaded on: December 4, 2022
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October 7, 2006 (v1)Conference paper
One important challenge in data mining is to extract interesting knowledge and useful information for expert users. Since data mining algorithms extracts a huge quantity of patterns it is therefore necessary to filter out those patterns using various measures. This paper presents IMAK, a part-way interestingness measure between objective and...
Uploaded on: December 4, 2022 -
2007 (v1)Book section
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)...
Uploaded on: December 4, 2022 -
April 1, 2009 (v1)Journal article
This paper presents the KEOPS data mining methodology centered on domain knowledge integration. KEOPS is a CRISP-DM compliant methodology which integrates a knowledge base and an ontology. In this paper, we focus first on the pre-processing steps of business understanding and data understanding in order to build an ontology driven information...
Uploaded on: December 4, 2022 -
June 12, 2008 (v1)Conference paper
This paper deals with knowledge integration in a data mining process. We suggest to model domain knowledge during business understanding and data understanding steps in order to build an ontology driven information system (ODIS). We present the KEOPS Methodology based on this approach. In KEOPS, the ODIS is dedicated to data mining tasks. It...
Uploaded on: December 4, 2022 -
2009 (v1)Book section
This paper presents the KEOPS data mining methodology centered on domain knowledge integration. KEOPS is a CRISP-DM compliant methodology which integrates a knowledge base and an ontology. In this paper, we focus first on the pre-processing steps of business understanding and data understanding in order to build an ontology driven information...
Uploaded on: December 4, 2022 -
January 17, 2006 (v1)Conference paper
Le Système d'Information Conceptuel ExCIS pour l'extraction de connaissances est une approche s'inspirant de CRISP- DM et intégrant le support des ontologies. Il permet de définir une ontologie de représentation des connaissances expertes du domaine, prenant en compte les besoins de la fouille de donnée, afin d'améliorer la pertinence des...
Uploaded on: December 3, 2022 -
June 8, 2008 (v1)Conference paper
In this paper, we firstly present what is interactive evolutionary computation (IEC) and rapidly how we have combined this artificial intelligence technique with an eye-tracker for visual optimization. Next, in order to correctly parameterize our application, we present results from applying data mining techniques on gaze information coming...
Uploaded on: December 4, 2022 -
November 25, 2005 (v1)Conference paper
In this paper, we present the new ontology-based methodology ExCIS (Extraction using a Conceptual Information System) for integrating expert prior knowledge in a data mining process. This methodology describes guidelines for a data mining process like CRISP-DM. Its originality is to build a specific conceptual information system related to the...
Uploaded on: December 3, 2022 -
2004 (v1)Conference paper
@inproceedings{AI-HEBERT-2004, author = {Brisson, L. and Pasquier, N. and Hébert, C. and Collard, M.}, title = {HASAR: mining sequential association rules for atherosclerosis risk factor analysis}, booktitle = {PKDD'04 Discovery Challenge on risk factors of patients with atherosclerosis co-located with the 8th European Conference on Principles...
Uploaded on: December 4, 2022 -
August 25, 2015 (v1)Conference paper
In this paper, we focus on the very specificity of rumors as pieces of information for modeling their process of propagation. We consider a population of pedestrians walking in a city and we assume that a rumor is transmitted by word of mouth from one to another. Although the diffusion of a rumor is of course a multi-dimensional process driven...
Uploaded on: February 22, 2023 -
December 18, 2008 (v1)Journal article
Biology is now an information-intensive science and various research areas, like molecular biology, evolutionary biology or environmental biology, heavily depend on the availability and the efficient use of information. Data mining, that regroups several techniques for analyzing very large datasets, is used to solve problems in an increasing...
Uploaded on: December 3, 2022 -
2017 (v1)Conference paper
The study of information dissemination in social networks is of particular importance in many areas as marketing, politics and security for example. Various strategies are being developed to disseminate information, those aimed at disseminating information widely and those aimed at disseminating information in a more confidential manner to make...
Uploaded on: December 3, 2022 -
September 20, 2004 (v1)Conference paper
We present the HASAR method that is an hybrid approach for ex- tracting adaptive sequential association rules. This method extracts association rules between events occurring in subsequent time-intervals using closed itemsets extraction and evolutionary techniques. An important feature is its capacity to consider different time-intervals...
Uploaded on: December 4, 2022 -
2004 (v1)Conference paper
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Uploaded on: October 11, 2023 -
2004 (v1)Conference paper
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Uploaded on: December 2, 2022 -
September 24, 2004 (v1)Conference paper
This paper addresses the problem of the integration of expert knowledge in a data mining process. We present the KTA ( integrating expert Knowledge in Transcriptome analysis) framework which allows the mining process to be driven by prior knowledge on the application domain. KTA is embedded in the MEDIANTE project for evaluating and using DNA...
Uploaded on: December 4, 2022