International Conference Papers

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Towards Big Data Analytics over Mobile User Data using Machine Learning
(IEEE, 2023-01) Ichou, Sabrina; Hammoudi, Slimane; Cuzzocrea, Alfredo; Meziane, Abdelkrim; Benna, Amel
Machine Learning (ML) is a science that forces computers to learn and behave like humans. As these systems interact with data, networks, and people, they automatically become smarter so that they can eventually solve or predict a practical issue in the world for us. The use of ML can be a giant leap for cannot simply be integrated as the top layer. This requires redefining workflow, architecture, data collection and storage, analytics, and other modules. This paper aims to discuss the issue of machine learning technique for analysis data of mobile user. First, we identified the machine learning benefits and drawbacks, challenges, advantages of using Machine Learning. Then, we propose a generic model of analytic mobile user data using ML, the model is centered on the machine learning component, which interacts with two other components, including mobile user data, and system. The interactions go in both directions. For instance, mobile user data serves as inputs to the learning component and the latter generates outputs; system architecture has impact on how learning algorithms should run and how efficient it is to run them, and simultaneously meeting. Mobile user data goes through several stages: prepossessing which includes the steps we need to follow to transform or encode the data so that it can be easily analyzed by the machine. Then, modelling in this step we will be clustering and classification the data obtained. Finally, evaluation, various measures of performance, accuracy, recall, precision, and F-measure were used to analyze the results of the naive Bayes, SVM, and K-nearest neighbor classification algorithms.
On the challenges of mobility prediction in smart cities
(Copernicus Publications, 2020) Boukhedouma, H.; Meziane, Abdelkrim; Hammoudi, S.; Benna, Amel
The mass of data generated from people’s mobility in smart cities is constantly increasing, thus making a new business for large companies. These data are often used for mobility prediction in order to improve services or even systems such as the development of location-based services, personalized recommendation systems, and mobile communication systems. In this paper, we identify the mobility prediction issues and challenges serving as guideline for researchers and developers in mobility prediction. To this end, we first identify the key concepts and classifications related to mobility prediction. We then, focus on challenges in mobility prediction from a deep literature study. These classifications and challenges are for serving further understanding, development and enhancement of the mobility prediction vision.
An Approach to Improve Business Process Models Reuse Using LinkedIn Social Network
(Springer International Publishing AG 2017, Editors: Rocha, Á., Correia, A.M., Adeli, H., Reis, L.P., Costanzo, S. (Eds.), 2017-04) Khider, Hadjer; Benna, Amel; Meziane, Abdelkrim; Hammoudi, Slimane
Business process (BP) modeling is an important stage in Business Process Management (BPM) lifecycle. However, modeling BP from scratch is fallible task, complex, time-consuming and error prone task. One of the promising solutions to these issues is the reuse of BP models. BP reusability during the BP modeling stage can be very useful since it reduces time and errors modeling, simplify users’ modeling tasks, improve the quality of process models and enhance modeler’s efficiency. The main objective of this paper is to propose a Social BPM approach based on the user social profile to perform the reuse of BP models. We identify the need of exploring user profile to reuse BP models. The LinkedIn social network is used to extract the users’ business interests. These user business interests are then used to recommend the appropriate BP model.
Social Business Process Management Approaches: A Comparative Study
(Edited by Slimane Hammoudi, Leszek Maciaszek and Ernest Teniente, 2015-04-27) Khider, Hadjer; Benna, Amel
The rapid development of web 2.0 in recent years has led fundamental changes and enormous opportunities in the way the business process models are available to the individuals and organizations. These organizations are looking increasingly to employ these technologies to enhance and improve their traditional Business Process Management. This idea has recently grown due to the characteristics of social software such as: weak ties and implicit knowledge, transparency, knowledge sharing, these features can be the motivation to socialize the classic Business Process Management (BPM) models. In this position paper we discuss the interaction of social software with BPM lifecycle phases (design, configuration, enactment, and evaluation) and how BPM can capitalize from social software.
SAWSDL et médiation pour la découverte des services Web
(2008-04-28) Benna, Amel; Boudjlida, Nacer; Talantikite, Hassina
Les services Web ont été adoptés par les plus grandes organisations industrielles et commerciales pour l’interopérabilité des systèmes distribués. L’interaction entre leurs composants s’effectue à travers la publication, la recherche et la découverte puis l’invocation. Cependant, leur publication dans l’UDDI ne propose pas une description du service sur la base de ce qu'il offre. L’idée rapportée dans cet article, est d’effectuer une description sémantique des services Web (en SAWSDL) et un stockage des fonctionnalités des services Web, lors de la phase de publication, dans un registre que nous avons appelé base de liens sémantiques. La découverte des services revient à l’interrogation de cette base, qui représente le médiateur entre demandeur et fournisseur de services, et du registre UDDI. Le résultat retourné peut servir de point d’entrée pour une autre interrogation.
Using tags Associated to Resources to Build Ontologies
(2014-08-11) Keddari, Djalila; Mellah, Hakima; Benna, Amel
Social tagging has recently emerged in collaborative web (Web 2.0) as a support shared resources organization allowing users to categorize these resources (web pages, video, images) by associating them with keywords, called tags. However, the use of uncontrolled tags poses several problems, namely ambiguity, writing variations (many tags denoting the same concept) as well as tags volume. The latter has led to tags classification into several clusters using the K-Means algorithm. The purpose of this work is that from tags clusters and their hierarchical classification, it would be important to build an ontology as these tags have a semantic aspect and are expressed by users who used the tagged resources. Building ontologies based on resource tag is a way to make automatic their building without requiring experts in their building as usual. Reproducing these tags clusters into ontological form is a way to share its knowledge with other users. We aim through this paper to build an ontology based on tags. A technical approach to form ontological portions, starting from tags clusters is based on semantic distance existing between tags. As tags clusters have a semantic relationship, the semantic distance between clusters is used to merge ontological portions into a global ontology
Matching Resources in Social Environment
(2012-06-28) Benna, Amel; Mellah, Hakima; Choui, Islam; Oualid, Ali
User comments on the web are becoming more and more important. We focus, in this paper, on the use of user-defined tags for annotating resources to identify links between them. These links are based on a social context of the resource, obtained by applying k-means classification method and a hierarchi- cal classification of tags within a cluster. The resources are re-assigned to this classification to facilitate the search process. The ranking of results is performed according to their degree of relevance, by evaluating a similarity score between the tagged contents, in hierarchical clusters of tags, and the user request. The re- sults of the evaluation, on the social bookmarking systemdel.icio.us, demonstrate significant improvements over traditional approaches.
An Ontology and a Description Schema Base for Relational Database Integration
(IEEE, 2008-04-19) Salhi, Nadir; Benna, Amel; Alimazighi, Zaia; Amrouche, Bilal; Makhloufi, Ferhat
Distributed Data sources integration is a method aiming to offer access for users to multiple databases through requests on a global schema. The use of an ontology is seamlessly the most promising approach for a possible automation to deal with the semantic heterogeneity, considered as the most important difficulty. In this paper we propose approach uses a domain ontology to solve semantic conflicts considered as a global schema and a description schema base in order to manage the mappings, done manually by the administrator of every relational source, between the global schema and the different databases. Moreover, we describe the algorithms related to relevant sources localization, requests decomposition, inter-sources joint, requests rewriting and recomposition of the results as tuples. Finally, we present a prototype for relational databases integration.
SAWSDL, mediation and XQUERY for web services discovery
(ACM, 2008-06) Benna, Amel; Boudjlida, Nacer; Talantikite, Hassina
Web services have been adopted by large industrial and commercial organizations to achieve interoperability between distributed systems. The interaction between web services components is done through publication, research, discovery and then invocation based on the service's description. However, their publication in an UDDI registry doesn't offer enough description of the service offering. The main idea described in this paper is about having a semantic description of web services (using SAWSDL) and then storing their functionality, during the publication phase, in a register named 'semantic links base'. This base represents the mediator between the service requestor and the service provider and would minimize the search time during the discovery step, because the mapping between the request concepts and the Web services are known in advance. The Web services discovery process is about finding these mappings between the user query, which is defined in a unified manner by referring to an ontology, and the web services functionality. The user request is translated into a query on the 'semantic links base' as well as the UDDI registry. The result returned can then be used as entry point for another query.
Building a social network, based on collaborative tagging, to enhance social information retrieval
(2012-03-24) Benna, Amel; Mellah, Hakima; Hadjari, Karima
Web 2.0 technologies put user at the center of data production and introduce a strong social collaboration. Therefore, the techniques used in traditional information retrieval systems do not meet the requirements of users who want to take into account their social preferences. The idea reported in this paper is to include not only the social context of the user but also that of the resource. In the social network that we consider, the user social context brings his interests, which are captured from a collaborative tagging system, while the resource social context is related to clusters of tags, obtained by classification method, and users’ opinions according to their expertise level on the resource. The results of our experiment evaluation on real-world datasets (crawled from delicious folksonomy) demonstrate significant improvements over traditional retrieval approaches.

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