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Publications of Author

1. Rabie Saidi, Mondher Maddouri, Engelbert Mephu Nguifo
   Classification supervisée de séquences biologiques basée sur les motifs et les matrices de substitution. [Citation Graph (0, 0)][DBLP]
   EGC, 2007, pp:409-420 [Conf]
   
2. Mondher Maddouri, Fatma Kaabi
   On Statistical Measures for Selecting Pertinent Formal Concepts to Discover Production Rules from Data. [Citation Graph (0, 0)][DBLP]
   ICDM Workshops, 2006, pp:780-784 [Conf]
   
3. Rabie Saidi, Mondher Maddouri, Engelbert Mephu Nguifo
   Biological Sequences Encoding for Supervised Classification. [Citation Graph (0, 0)][DBLP]
   BIRD, 2007, pp:224-238 [Conf]
   
4. Mondher Maddouri
   Towards a machine learning approach based on incremental concept formation. [Citation Graph (0, 0)][DBLP]
   Intell. Data Anal., 2004, v:8, n:3, pp:267-280 [Journal]
   
5. Mondher Maddouri, Samir Elloumi, Ali Jaoua
   An Incrementa Learning System for Imprecise and Uncertain Knowledge Discovery. [Citation Graph (0, 0)][DBLP]
   Inf. Sci., 1998, v:109, n:1-4, pp:149-164 [Journal]
   
6. Mondher Maddouri, Mourad Elloumi
   Encoding of Primary Structures of Biological Macromolecules Within a Data Mining Perspective. [Citation Graph (0, 0)][DBLP]
   J. Comput. Sci. Technol., 2004, v:19, n:1, pp:78-88 [Journal]
   
7. Mourad Elloumi, Mondher Maddouri
   New voting strategies designed for the classification of nucleic sequences. [Citation Graph (0, 0)][DBLP]
   Knowl. Inf. Syst., 2005, v:8, n:1, pp:1-15 [Journal]
   
8. Mondher Maddouri, Mourad Elloumi
   A data mining approach based on machine learning techniques to classify biological sequences. [Citation Graph (0, 0)][DBLP]
   Knowl.-Based Syst., 2002, v:15, n:4, pp:217-223 [Journal]
   
9. Mondher Maddouri, Jamil Gammoudi
   On Semantic Properties of Interestingness Measures for Extracting Rules from Data. [Citation Graph (0, 0)][DBLP]
   ICANNGA (1), 2007, pp:148-158 [Conf]
   
10. 
    Improving Boosting by Exploiting Former Assumptions. [Citation Graph (, )][DBLP]
    
    
11. 
    Une nouvelle approche du Boosting face aux données réelles. [Citation Graph (, )][DBLP]
    
    
12. 
    Apprentissage supervisé adaptatif de Concepts Formels à partir des données nominales. [Citation Graph (, )][DBLP]
    
    
13. 
    Générer des règles de classification par dopage de concepts formels. [Citation Graph (, )][DBLP]
    
    
14. 
    Etude de stabilité de méthodes d'extraction de motifs à partir des séquences protéiques. [Citation Graph (, )][DBLP]
    
    
15. 
    Développement de méthodes de classification basées sur l'analyse de concepts formels sous la plateforme WEKA. [Citation Graph (, )][DBLP]
    
    
16. 
    Boosting Formal Concepts to Discover Classification Rules. [Citation Graph (, )][DBLP]
    
    
17. 
    Incremental Rule Production: Towards a Uniform Approach for Knowledge Organization. [Citation Graph (, )][DBLP]
    
    
18. 
    Comparing graph-based representations of protein for mining purposes. [Citation Graph (, )][DBLP]
    
    
19. 
    Protein sequences classification by means of feature extraction with substitution matrices. [Citation Graph (, )][DBLP]