The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON BIOLOGY AND BIOMEDICINE
Transactions ID Number: 28-898
Full Name: Anas Dahabiah
Position: Ph.D. Candidate
Age: ON
Sex: Male
Address: Dahabiah, 227, Rue Jean JAURES, 29200, Brest, France
Country: FRANCE
Tel: +33625563984
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E-mail address: dahabiah@hotmail.com
Other E-mails: anas.dahabiah@telecom-bretagne.eu
Title of the Paper: Digestive Database Evidential Clustering Based on Possibility Theory
Authors as they appear in the Paper: Anas Dahabiah, John Puentes, and Basel Solaiman
Email addresses of all the authors: Anas.DAHABIAH@telecom-bretagne.eu , john.puentes@telecom-bretagne.fr, basel.solaiman@telecom-bretagne.fr
Number of paper pages: 10
Abstract: A new method that aims to automatically classify a set of objects in spite of the imperfection and the uncertainty of their heterogeneously-assigned data is proposed in this paper. This method is based essentially on possibility theory to estimate the similarity among the objects, and on belief theory and multidimensional scaling methods to construct the compatible evidential class partition. This method is applied to a medical database and robust results have been obtained without knowing the key attributes of the concerned pathologies and without taking into account any a priori medical knowledge.
Keywords: Possibility Theory, Evidence Theory, Similarity, Clustering, Partition, Multi-Dimensional Scaling, Digestive Lesions, Endoscopic Images
EXTENSION of the file: .pdf
Special (Invited) Session: Possibilistic Evidential Clustering
Organizer of the Session: 609-414
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IP ADDRESS: 192.108.115.2
