ICT & Generative Artificial Intelligence Powered Hybrid Model for Future Education

The Hybrid Model, powered by Information and Communication Technology (ICT) for future education, enriched with Generative Artificial Intelligence (GAI), stands today as an advanced educational learning model. It ingeniously combines the strengths of ICT and generative AI to reshape the educational experience. Numerous academic institutions and organizations are embracing this transformative approach, harmonizing traditional classroom methods with state-of-the-art technologies and AI-driven innovations. In this study, we present an in-depth exploration of this novel ICT-powered hybrid model boosted by generative AI, dissecting its intricate components. We endeavor to unravel the advantages it bestows upon both students and educators, attempting to answer the pivotal question: what added value does this hybrid model bring to education? We embark on a meticulous enumeration of the diverse challenges encountered along the path of implementing this modern model. Additionally, we underscore the critical considerations that stakeholders must consider when deploying this educational evolution effectively

La composition de service pour les utilisateurs finaux, basée sur l'analyse des réseaux sociaux

Service composition has risen from the need to make information systems more flexible and open. The Service Oriented Architecture has become the reference architecture model for applications carried by the impetus of Internet (Web). In fact, information systems are able to expose interfaces through the Web which has increased the number of available Web services. On the other hand, with the emergence of the Web 2.0, service composition has evolved toward web users with limited technical skills. Those end-users, named Y generation, are participating, creating, sharing and commenting content through the Web. This evolution in service composition is translated by the reference paradigm of Mashup and Mashup editors such as Yahoo Pipes! This paradigm has established the service composition within end users community enabling them to meet their own needs, for instance by creating applications that do not exist. Additionally, Web 2.0 has brought also its social dimension, allowing users to interact, either directly through the online social networks or indirectly by sharing, modifying content, or adding metadata. In this context, this thesis aims to support the evolving concept of service composition through meaningful contributions. The main contribution of this thesis is indeed the introduction of the social dimension within the process of building a composite service through end users’ dedicated environments. In fact, this concept of social dimension considers the activity of compositing services (creating a Mashup) as a social activity. This activity reveals social links between users based on their similarity in selecting and combining services. These links could be an interesting dissemination means of expertise, accumulated by users when compositing services. In other terms, based on frequent composition patterns, and similarity between users, when a user is editing a Mashup, dynamic recommendations are proposed. These recommendations aim to complete the initial part of Mashup already introduced by the user. This concept has been explored through (i) a step-by-step Mashup completion by recommending a single service at each step, and (ii) a full Mashup completion approaches by recommending the whole sequence of services that could complete the Mashup. Beyond pushing a vision for integrating the social dimension in the service composition process, this thesis has addressed a particular constraint for this recommendation system which conditions the interactive systems requirements in terms of response time. In this regard, we have developed robust algorithms adapted to the specificities of our problem. Whereas a composite service is considered as a sequence of basic service, finding similarities between users comes first to find frequent patterns (subsequences) and then represent them in an advantageous data structure for the recommendation algorithm. The proposed algorithm FESMA, provide exactly those requirements based on the FSTREE structure with interesting results compared to the prior art. Finally, to implement the proposed algorithms and methods, we have developed a Mashup creation framework, called Social Composer (SoCo). This framework, dedicated to end users, firstly implements abstraction and usability requirements through a workflow-based graphic environment. As well, it implements all the mechanisms needed to deploy composed service starting from an abstract description entered by the user. More importantly, SoCo has been augmented by including the dynamic recommendation functionality, demonstrating by the way the feasibility of this concept.Le paradigme de service dans les nouvelles technologies de l’information et de communication est omniprésent, si bien qu’on parle de science des services. Les services Web sont définis dans le cadre des architectures orientées services (SOA) qui permet de distinguer le fournisseur de service, le répertoire de services, et enfin le consommateur du service. Cette distinction permet de créer de nouveaux services en composant des services déjà existants. Cependant, la composition de services est principalement bénéfique aux utilisateurs expérimentés comme les développeurs de logiciels car elle requiert un niveau technique élevé. Par opposition, la tendance actuelle traduite par l’émergence du Web2.0, vise à permettre aux utilisateurs du Web de créer leurs propres services à travers les environnements de Mashup, ou de collaborer et de capitaliser des connaissances à travers les réseaux et les médias sociaux. Nous croyons qu’il existe un grand potentiel pour “démocratiser” la composition de services dans de tels contextes. L’émergence du Web 2.0, basé sur des paradigmes tels que le contenu généré par l’utilisateur (UGC, Mashups) et le web social, constitue, une opportunité intéressante pour améliorer la productivité de services par l’utilisateur final et accélérer son processus créatif en capitalisant les connaissances générées par tous les utilisateurs. Dans ce contexte, cette thèse vise à soutenir l'évolution du concept de composition de services par le biais de contributions significatives. La principale contribution de cette thèse est en effet l'introduction de la dimension sociale dans le processus de construction d'un service composite à travers les environnements dédiés aux utilisateurs finaux. Ce concept considère l'activité de composition de services (création d'un Mashup) comme une activité sociale. Cette activité révèle les liens sociaux entre les utilisateurs en fonction de leur similitude dans le choix et la combinaison des services. Ces liens permettent de diffuser d'expertise de composition de services. En d'autres termes, sur la base des schémas fréquents de composition, et la similitude entre les utilisateurs, lorsqu’un utilisateur est en train d’éditer un Mashup, des recommandations dynamiques lui sont proposées. Ces recommandations visent à compléter la première partie de Mashup déjà mis en place par l'utilisateur. Ce concept a été exploré à travers (i) la complétion de Mashup étape par étape en recommandant à chaque étape un service unique, et (ii) la complétion totale de Mashup en recommandant la séquence complète de services qui pourraient le compléter. Au-delà de l’introduction de la dimension sociale dans le processus de composition de services, cette thèse a adressé une contrainte particulière du système de recommandation liée aux exigences des systèmes interactifs en termes de temps de réponse. À cet égard, nous avons développé des algorithmes robustes et adaptées aux spécificités de notre problème. Alors qu’un service composite est considéré comme une séquence de service, la recherche de similarités entre les utilisateurs revient d'abord à trouver des modèles fréquents, puis de les représenter dans une structure de données avantageuse pour l'algorithme de recommandation. L’algorithme proposé FESMA répond à ces exigences en se basant sur la structure FSTREE et offrant des résultats intéressants par rapport à l'art antérieur. Enfin, pour mettre en œuvre les algorithmes et les méthodes proposées, nous avons développé un environnement de création de Mashup, appelé ‘Social Composer’ (SoCo). Cet environnement, dédié aux utilisateurs finaux, respecte les critères d'utilisation en se basant sur le workflow graphique. En outre, il met en œuvre tous les mécanismes nécessaires pour déployer le service composé à partir d'une description abstraite introduite par l'utilisateur. De plus, SoCo a été augmentée en y incluant la fonctionnalité de recommandation dynamique, démontrant la faisabilité de ce concep

La composition de service pour les utilisateurs finaux, basée sur l'analyse des réseaux sociaux

Le paradigme de service dans les nouvelles technologies de l information et de communication est omniprésent, si bien qu on parle de science des services. Les services Web sont définis dans le cadre des architectures orientées services (SOA) qui permet de distinguer le fournisseur de service, le répertoire de services, et enfin le consommateur du service. Cette distinction permet de créer de nouveaux services en composant des services déjà existants. Cependant, la composition de services est principalement bénéfique aux utilisateurs expérimentés comme les développeurs de logiciels car elle requiert un niveau technique élevé. Par opposition, la tendance actuelle traduite par l émergence du Web2.0, vise à permettre aux utilisateurs du Web de créer leurs propres services à travers les environnements de Mashup, ou de collaborer et de capitaliser des connaissances à travers les réseaux et les médias sociaux. Nous croyons qu il existe un grand potentiel pour démocratiser la composition de services dans de tels contextes. L émergence du Web 2.0, basé sur des paradigmes tels que le contenu généré par l utilisateur (UGC, Mashups) et le web social, constitue, une opportunité intéressante pour améliorer la productivité de services par l utilisateur final et accélérer son processus créatif en capitalisant les connaissances générées par tous les utilisateurs. Dans ce contexte, cette thèse vise à soutenir l'évolution du concept de composition de services par le biais de contributions significatives. La principale contribution de cette thèse est en effet l'introduction de la dimension sociale dans le processus de construction d'un service composite à travers les environnements dédiés aux utilisateurs finaux. Ce concept considère l'activité de composition de services (création d'un Mashup) comme une activité sociale. Cette activité révèle les liens sociaux entre les utilisateurs en fonction de leur similitude dans le choix et la combinaison des services. Ces liens permettent de diffuser d'expertise de composition de services. En d'autres termes, sur la base des schémas fréquents de composition, et la similitude entre les utilisateurs, lorsqu un utilisateur est en train d éditer un Mashup, des recommandations dynamiques lui sont proposées. Ces recommandations visent à compléter la première partie de Mashup déjà mis en place par l'utilisateur. Ce concept a été exploré à travers (i) la complétion de Mashup étape par étape en recommandant à chaque étape un service unique, et (ii) la complétion totale de Mashup en recommandant la séquence complète de services qui pourraient le compléter. Au-delà de l introduction de la dimension sociale dans le processus de composition de services, cette thèse a adressé une contrainte particulière du système de recommandation liée aux exigences des systèmes interactifs en termes de temps de réponse. À cet égard, nous avons développé des algorithmes robustes et adaptées aux spécificités de notre problème. Alors qu un service composite est considéré comme une séquence de service, la recherche de similarités entre les utilisateurs revient d'abord à trouver des modèles fréquents, puis de les représenter dans une structure de données avantageuse pour l'algorithme de recommandation. L algorithme proposé FESMA répond à ces exigences en se basant sur la structure FSTREE et offrant des résultats intéressants par rapport à l'art antérieur. Enfin, pour mettre en œuvre les algorithmes et les méthodes proposées, nous avons développé un environnement de création de Mashup, appelé Social Composer (SoCo). Cet environnement, dédié aux utilisateurs finaux, respecte les critères d'utilisation en se basant sur le workflow graphique. En outre, il met en œuvre tous les mécanismes nécessaires pour déployer le service composé à partir d'une description abstraite introduite par l'utilisateur. De plus, SoCo a été augmentée en y incluant la fonctionnalité de recommandation dynamique, démontrant la faisabilité de ce conceptService composition has risen from the need to make information systems more flexible and open. The Service Oriented Architecture has become the reference architecture model for applications carried by the impetus of Internet (Web). In fact, information systems are able to expose interfaces through the Web which has increased the number of available Web services. On the other hand, with the emergence of the Web 2.0, service composition has evolved toward web users with limited technical skills. Those end-users, named Y generation, are participating, creating, sharing and commenting content through the Web. This evolution in service composition is translated by the reference paradigm of Mashup and Mashup editors such as Yahoo Pipes! This paradigm has established the service composition within end users community enabling them to meet their own needs, for instance by creating applications that do not exist. Additionally, Web 2.0 has brought also its social dimension, allowing users to interact, either directly through the online social networks or indirectly by sharing, modifying content, or adding metadata. In this context, this thesis aims to support the evolving concept of service composition through meaningful contributions. The main contribution of this thesis is indeed the introduction of the social dimension within the process of building a composite service through end users dedicated environments. In fact, this concept of social dimension considers the activity of compositing services (creating a Mashup) as a social activity. This activity reveals social links between users based on their similarity in selecting and combining services. These links could be an interesting dissemination means of expertise, accumulated by users when compositing services. In other terms, based on frequent composition patterns, and similarity between users, when a user is editing a Mashup, dynamic recommendations are proposed. These recommendations aim to complete the initial part of Mashup already introduced by the user. This concept has been explored through (i) a step-by-step Mashup completion by recommending a single service at each step, and (ii) a full Mashup completion approaches by recommending the whole sequence of services that could complete the Mashup. Beyond pushing a vision for integrating the social dimension in the service composition process, this thesis has addressed a particular constraint for this recommendation system which conditions the interactive systems requirements in terms of response time. In this regard, we have developed robust algorithms adapted to the specificities of our problem. Whereas a composite service is considered as a sequence of basic service, finding similarities between users comes first to find frequent patterns (subsequences) and then represent them in an advantageous data structure for the recommendation algorithm. The proposed algorithm FESMA, provide exactly those requirements based on the FSTREE structure with interesting results compared to the prior art. Finally, to implement the proposed algorithms and methods, we have developed a Mashup creation framework, called Social Composer (SoCo). This framework, dedicated to end users, firstly implements abstraction and usability requirements through a workflow-based graphic environment. As well, it implements all the mechanisms needed to deploy composed service starting from an abstract description entered by the user. More importantly, SoCo has been augmented by including the dynamic recommendation functionality, demonstrating by the way the feasibility of this concept.EVRY-INT (912282302) / SudocSudocFranceF

Fast and accurate business process drift detection

Business processes are prone to continuous and unexpected changes. Process workers may start executing a process differently in order to adjust to changes in workload, season, guidelines or regulations for example. Early detection of business process changes based on their event logs – also known as business process drift detection – enables analysts to identify and act upon changes that may otherwise affect process performance. Previous methods for business process drift detection are based on an exploration of a potentially large feature space and in some cases they require users to manually identify the specific features that characterize the drift. Depending on the explored feature set, these methods may miss certain types of changes. This paper proposes a fully automated and statistically grounded method for detecting process drift. The core idea is to perform statistical tests over the distributions of runs observed in two consecutive time windows. By adaptively sizing the window, the method strikes a trade-off between classification accuracy and drift detection delay. A validation on synthetic and real-life logs shows that the method accurately detects typical change patterns and scales up to the extent it is applicable for online drift detection

From Service Composition to Mashup Editor: A Multiperspective Taxonomy

Service-oriented computing has become a popular area of research, with a particular focus on service composition. There have been many developments in this field, such as new techniques for data engineering in service description languages, protocols for publication and discovery, the optimization of service selection and scheduling, and the deployment and monitoring of composed services. However, this diversity of approaches and methodologies can make it challenging to navigate between different proposed solutions and identify research gaps. In order to provide a clearer understanding of this body of work, this paper presents a comprehensive framework for the taxonomy of service composition approaches, methodologies, and tools. This framework proposes a structured view of different perspectives, such as formal, semantic, and automatic approaches, with a particular focus on the end-user’s perspective and tools such as Mashups

Detecting drift from event streams of unpredictable business processes

Existing business process drift detection methods do not work with event streams. As such, they are designed to detect inter-trace drifts only, i.e. drifts that occur between complete process executions (traces), as recorded in event logs. However, process drift may also occur during the execution of a process, and may impact ongoing executions. Existing methods either do not detect such intra-trace drifts, or detect them with a long delay. Moreover, they do not perform well with unpredictable processes, i.e. processes whose logs exhibit a high number of distinct executions to the total number of executions. We address these two issues by proposing a fully automated and scalable method for online detection of process drift from event streams. We perform statistical tests over distributions of behavioral relations between events, as observed in two adjacent windows of adaptive size, sliding along with the stream. An extensive evaluation on synthetic and real-life logs shows that our method is fast and accurate in the detection of typical change patterns, and performs significantly better than the state of the art

Analysis of business process variants in apromore

In this paper we illustrate a set of features of the Apromore process model repository for analyzing business process variants. Two types of analysis are provided: one is static and based on differences on the process control flow, the other is dynamic and based on differences in the process behavior between the variants. These features combine techniques for the management of large process model collections with those for mining process knowledge from process execution logs. The tool demonstration will be useful for researchers and practitioners working on large process model collections and process execution logs, and specifically for those with an interest in understanding, managing and consolidating business process variants both within and across organizational boundaries

Local Concurrency Detection in Business Process Event Logs

Process mining techniques aim at analysing records generated during the execution of a business process in order to provide insights on the actual performance of the process. Detecting concurrency relations be- tween events is a fundamental primitive underpinning a range of process mining techniques. Existing approaches to this problem identify concur- rency relations at the level of event types under a global interpretation. If two event types are declared to be concurrent, every occurrence of one event type is deemed to be concurrent to one occurrence of the other. In practice, this interpretation is too coarse-grained and leads to over- generalization. This paper proposes a finer-grained approach, whereby two event types may be deemed to be in a concurrency relation relative to one state of the process, but not relative to other states. In other words, the detected concurrency relation holds locally, relative to a set of states. Experimental results both with artificial and real-life logs show that the proposed local concurrency detection approach improves the accuracy of existing concurrency detection techniques