Academic & Scientific Articles

Permanent URI for this communityhttp://dl.cerist.dz/handle/CERIST/3

Browse

Author: search.filters.author.Benna, Amel

Search Results

Now showing 1 - 10 of 22
  • Thumbnail Image
    Item
    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.
  • Thumbnail Image
    Item
    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.
  • No Thumbnail Available
    Item
    Social Business Process Model Recommender: An MDE approach
    (CERIST, 2018-09-26) Khider, Hadjer; Hammoudi, Slimane; Benna, Amel; Meziane, Abdelkrim
    with the advent of the social Web (Web 2.0) and the massive use of online social networks (OSNs) (e.g.Facebook, LinkedIn). OSNs have become new opportunity that provides huge Masses of data about users’, rich in their diversity and important in their quantity. Exploring the profiles data among these OSNs attract a great deal of attention among researchers in several research areas: social information retrieval systems, social recommendation systems. Social Recommender Systems aim to generate meaningful recommendations to a collection of users for items that might be interesting for them. In this paper we propose to investigate social recommender systems for improving Business process (BP) models reuse in process models repositories. The recommender system we propose to integrate we called SBPR recommender. SBPR recommender aims to recommend to the users of such repositories BP models for reuse. LinkedIn User profile is the source of social data for SBPR recommender; BP models are target items to be recommended to user. We propose a framework based on Model Driven Engineering (MDE) approach where techniques of models, metamodels, transformation and weaving are used to implement a generic recommendation process.
  • Thumbnail Image
    Item
    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.
  • Thumbnail Image
    Item
    Toward an Approach to Improve Business Process Models Reuse Based on Linkedin Social Network
    (CERIST, 2017-01-10) Khider, Hadjer; Benna, Amel; Meziane, Abdelkrim; Hammoudi, Slimane
    Business process (BP) modeling is an important stage in 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 Business Process Management (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.
  • Thumbnail Image
    Item
    Survey and comparative study of Business process models repositories
    (CERIST, 2016-12-21) Khider, Hadjer; Benna, Amel
    A Business Process (BP) modeling is a complicated task, time-consuming, and error prone task. One of the promising solutions to overcome these challenges is by the reuse of BP models, consequently, it is important to provide a BP models repository to store thousands of BP models for business actors (e.g. analysts, modelers, managers, and process developers) to find existing business processes. In this report, we present a survey and a comparative study of existing BP models. We present also the limitations that affect BP models reuse in these repositories.
  • Thumbnail Image
    Item
    A MOF-based Social Web Services Description Metamodel
    (CERIST, 2015-12-09) Benna, Amel; Maamar, Zakaria; Ahmed-Nacer, Mohamed
    To make IT community adopt social Web services, both social Web service-based applications and their support platforms should evolve independently from each other while sharing a common model that represent the characteristics of these social Web services. This paper proposes a model-driven approach that achieves this duality. First, the approach identifies a social Web service's properties. Then a Meta-Object-Facility(MOF)-based social Web services description metamodel is developed. A prototype illustrates how the proposed MOF-based metamodel is used.
  • Thumbnail Image
    Item
    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.
  • Thumbnail Image
    Item
    Social Business Process Management Approaches: A Comparative Study
    (CERIST, 2015-02-25) 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.
  • Thumbnail Image
    Item
    Collaboration sociale dans un échange inter intra entreprises
    (CERIST, 2014-06-20) Khider, Hadjer; Benna, Amel
    Les plateformes du Web 2.0 ont favorisé le développement des logiciels sociaux. Ces techniques permettent de mettre en relation des personnes partageant les mêmes centres d’intérêt personnels ou professionnels, ce qui met les utilisateurs au centre de la production de données. Cependant les systèmes de gestion des processus métiers classiques ne prennent pas les préférences des utilisateurs en considération. L’aspect social est un facteur important à prendre en considération pour améliorer les échanges et collaboration inter entreprises afin de mieux répondre aux besoins et intérêts des utilisateurs, qui veulent voir leurs préférences prises en compte. La gestion des processus métiers n'a pas beaucoup en commun avec les logiciels sociaux. Cependant, si l'intégration des logiciels sociaux et BPM est réalisée avec succès, un certain nombre d'avantages pour la gestion des processus métiers peuvent être apportés. Les logiciels sociaux et les BPM peuvent être utilisés de façons complémentaires pour supporter le travail collaboratif dans les organisations. Le logiciel social peut être utilisé pour pallier les lacunes des approches traditionnelles de la BPM. Dans ce rapport nous identifions et étudions comment les logiciels sociaux et les BPM peuvent être utilisés de façons complémentaires pour supporter le travail collaboratif dans des organisations et présenter ensuite les différentes approches qui ont inclus l’aspect social dans l’échange et collaboration inter entreprises.