An Aspect-Oriented Approach for Dynamic Monitoring of a Service Logic Execution Environment

Service creation environments play a relevant role in new telecom applications because they enable openness and programmability by offering frameworks for the development of value added services. The JAIN SLEE specification defines a Java framework for executing event-based distributed services made up of components, called Service Building Blocks. In such a complex architecture, monitoring is an indispensable technique to test the dynamic behavior of a system, debug the code, gather usage statistics or measure the quality of service. Program instrumentation is needed to insert monitoring code into the system to be monitored, which is typically a manual and time-consuming task. This paper describes a language-based approach to automate program instrumentation and monitoring management using a dynamic Aspect Oriented Programming (AOP) framework. The basic notions of AOP and the use of the JBoss AOP framework features are described, in order to allow a highly modular and easily configurable implementation of reusable monitoring code. Using an Eclipse-based system administration console, it is possible to manage remotely the dynamic deployment and update of monitoring code in a service deployed on a JAIN-SLEE container

Situation Inference for Mobile Users: a Rule Based Approach

Mobile phones are being increasingly equipped with sensors that ease retrieval of context information about a user. Context data can be aggregated with information centrally available to mobile operators and service providers, to infer higher-level information such as user “situations”, easier to integrate with services. We have been conducting an internal trial monitoring the context of different users in their business life and designing rules to infer high level situations: logical location, activity and social state. In this paper we present the infrastructure and the rulebased reasoning process used for this experiment

User-Centric Future Internet and Telecommunication Services

This paper analyses the current service creation trends in telco and Web worlds, showing how they are converging towards a future Internet of usercentric services embracing typical telco capabilities. The OPUCE platform is presented as the next step towards this integrated, user-centric future: a platform which offers intuitive tools for graphical service creation aimed at individuals with no specific skills in computer science or programming and a serviceoriented execution environment capable of a seamless interoperation of Web Services and telco applications based on operator-owned infrastructure. The OPUCE platform is compared to existing mashup creation tools to show its advantages and how is compared to existing mashup creation tools to show its advantages and how it could be used to implement a converged and open service marketplace for the Future Internet

Introducing the user to the service creation world: concepts for user centric service creation, personalization and notification

The “Web 2.0” feature that most permeates the nowadays web is “user-centricity”. Now users are not only consumers of items (software, information, etc.), but also creators of those items. This paper intends to push this paradigm further, targeting mashups of telco and web services in a unique service environment where personalised services will be dynamically created and provisioned by end-users themselves, regardless of ambiance and location. The paper explains how user-centricity can be applied to the service creation world and in general to the overall service lifecycle process. It also describes the platform being implemented in the OPUCE project that captures this philosophy and will be submitted to end-user validation. Whilst focusing on intuitive editors for end-users to compose services, additional hints are provided about personalization and notification approaches to improve user centricity

Traduction d'un jeu de données de dialogues en français et Détection d'émotion à partir de texte

International audienceLes chatbots permettent à un programme informatique d'interagir plus naturellement avec un interlocuteur. Ils demeurent toutefois limités, n'étant pas sensibles à l'état d'esprit ou aux émotions de l'utilisateur, ce qui leur permettrait pourtant d'apporter des réponses plus pertinentes. La détection d'émotion sur des discussions textuelles a déjà été explorée pour l'anglais (SemEval 2019 Task 3), mais en français aucun dataset satisfaisant n'est disponible. Nous proposons de traduire le dataset de dialogues EmotionLines, dont les répliques anglaises sont issues de la série Friends, en exploitant sa diffusion en VF. Notre méthode de génération de dataset par traduction est adaptable à tout dataset tiré de séries ou films étrangers disponibles en VF. En utilisant ce dataset traduit, nous proposons un classifier basé sur le modèle de langage BERT, permettant de détecter l'émotion de l'utilisateur à partir de texte. Il tient compte du contexte de la discussion pour affiner ses prédictions. 1. https://deft.limsi.fr/2015/corpus.fr.php?lang=fr. 2. EmotionX et MELD sont des améliorations d'EmotionLines : ils reposent sur les mêmes dialogues et répliques