Amine Chikh

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Web services are becoming the most important paradigm for distributed computing and electronic business. They are self-contained Internet accessible applications that are capable not only of performing business activities on their own, but they also possess the ability to engage with other Web services in order to build new value-added services. In this(More)
—The use of expert systems and artificial intelligence techniques in disease diagnosis has been increasing gradually. Artificial Immune Recognition System 2 (AIRS2) is one of the methods used in medical classification problems. In this paper, we used a Modified AIRS2 (MAIRS2) where we replace the K-nearest neighbors algorithm with the fuzzy K-nearest(More)
This paper presents a fuzzy rule based classifier and its application to discriminate premature ventricular contraction (PVC) beats from normals. An Adaptive Neuro-Fuzzy Inference System (ANFIS) is applied to discover the fuzzy rules in order to determine the correct class of a given input beat. The main goal of our approach is to create an interpretable(More)
Web services are taking an important place in the distributed computing field, as well as in the electronic business. In this work we present an initial research which deals with the issue of automated service retrieval. For that, we propose an approach which exploits the service interface (inputs/outputs) and the domain ontology, in order to index(More)
In this paper, we present the methods that we have proposed and used in the liver image annotation task of ImageCLEF 2015.This challenge entailed the annotation of liver CT scans to generate a structured report. To meet this challenge we have proposed two methods for annotating the liver image. The first one uses a classification approach, which is composed(More)
In the context of arabic Information Retrieval Systems (IRS) guided by arabic ontology and to enable those systems to better respond to user requirements, this paper aims to representing documents and queries by the best concepts extracted from Arabic Wordnet. Identified concepts belonging to Arabic WordNet synsets are extracted from documents and queries,(More)