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Bouyahia Z.,SOIE Laboratory | Bellalouna M.,SOIE Laboratory | Ghedira K.,High Institute of Management
Computers and Industrial Engineering | Year: 2013

Abstract In a previous work (Bouyahia et al., 2010), we introduced and studied the probabilistic generalization of the classical total weighted completion time problem. We defined two a priori strategies devoted to the incorporated problem on parallel identical machines (UA and UB). The main drawback of the proposed a priori strategies is that the machine loads are not balanced after deleting the absent jobs from an a priori schedule. In this paper, we try to overcome this limitation by proposing an a priori strategy denoted as Uk which takes into account the load balance. First, we present the algorithm of the load balancing strategy and we explicit the objective function. Then, we study its complexity and its performance compared to the other strategies. Special care is also devoted to assess experimentally the performance of Uk. © 2012 Elsevier Ltd. All rights reserved. Source


Ayadi N.Y.,National School in Computer Science | Charrad M.,National School in Computer Science | Vidal M.-E.,Simon Bolivar University of Venezuela | Ahmed M.B.,National School in Computer Science | Amdouni S.,High Institute of Management
Information Interaction Intelligence | Year: 2011

The success of Web service technology has brought a lot of interest from a large number of research communities such as Software Engineering, Artificial Intelligence, Semantic Web, Semantic Grid, etc. Despite several efforts towards automating service discovery and composition, users still search for services via online repositories and compose them manually. In our opinion, this is due to the lack of semantic annotations (metadata) to describe service semantics and support an effective and efficient discovery of services. Semantic annotation is commonly recognized as one of the cornerstones of the semantic Web and also, an expensive, time consuming and error prone process. Thus, approaches to automatically derive annotations that would describe rapidly changing Web services repositories are extremely required. In this paper, we propose a semantic framework for bioinfor-matics Web service annotation, matching and classification. We propose a semi-automatic extraction approach of lightweight semantic annotations from textual description of Web services. We investigate the use of NLP techniques to derive service properties given a corpus of textual description of bioinformatics services. We evaluate the performance of the annotation extraction method and the importance of lightweight annotations to match, reason and classify bioinformatics Web services in order to bootstrap the service discovery process. Based on extracted annotations, we propose an inference and block clustering approaches, the two approaches are complementary. The former relies on semantic annotations and explicit background knowledge to match a discovery query and a set of Web services. The latter approach aims to deduce implicit associations between services and annotations highly correlated by applying an accelerated version of the Croki2 algorithm. Source


Nakhla Z.,High Institute of Management | Nouira K.,High Institute of Management
Proceedings of 2014 Science and Information Conference, SAI 2014 | Year: 2014

Ontology Based DataBase (OBDB) is a database model that allows both ontologies, which is a formal representation of terms related to specific domain, and their instances to be stored and queried in a single database. In this paper, we propose the construction of OBDB for the development of medical system. The idea is to automatically construct OBDB using rules and used it in the construct of medical system. To demonstrate the relevance of the proposed approach, we compare with current approaches of OBDB. © 2014 The Science and Information (SAI) Organization. Source


Josang A.,University of Oslo | Elouedi Z.,High Institute of Management
Fusion 2011 - 14th International Conference on Information Fusion | Year: 2011

Material implication is traditionally denoted as (x→y), where x represents the antecedent and y the consequent of the logical relationship between the propositions x and y. Material implication is a truth functional connective, meaning that it is defined by a truth table. While truth functional connectives normally have a relatively clear interpretation in normal language, this is not the case for material implication. It could for example be expressed as: "if x is true, then y is true". However, this does not say anything about the case when x is false, which is problematic for the interpretation of the corresponding entries in the truth table. In this paper we introduce a probabilistic view of material implication and show that it is not closed under binary truth values, and that it in fact produces uncertainty in the form of a vacuous opinion. When seen in this light, it becomes clear that the traditional definition of material implication is based on the over-simplistic and misleading interpretation of complete uncertainty as binary logic TRUE. We redefine material implication with subjective logic to preserve the uncertainty that it unavoidably produces in specific cases. We then compare the new definition of material implication with conditional deduction, and show that they reflect the same mathematical equation rearranged in different forms. © 2011 IEEE. Source


Karaa W.B.A.,High Institute of Management | Mhimdi N.,High Institute of Management
International Journal of Metadata, Semantics and Ontologies | Year: 2011

Employers collect a large number of resumes from job portals or from their company's own website. These documents are used for an automated selection of candidates satisfying the requirements and therefore reducing recruitment costs. Various approaches for process documents have already been developed for recruitment. In this paper, we present an approach based on semantic annotation of resumes for an e-recruitment process. The most important task consists of modelling the semantic content of these documents using ontology. The ontology is built taking into account the most significant components of resumes inspired from the structure of EUROPASS CV. This ontology is thereafter used to annotate automatically the resumes. Copyright © 2011 Inderscience Enterprises Ltd. Source

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