Social Business Process Model Recommender: An MDE approach

dc.contributor.authorKhider, Hadjer
dc.contributor.authorHammoudi, Slimane
dc.contributor.authorBenna, Amel
dc.contributor.authorMeziane, Abdelkrim
dc.description.abstractwith 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.fr_FR
dc.identifier.isrnCERIST- DSISM/RR-18-00000008--DZfr_FR
dc.relation.ispartofRapports de recherche internes
dc.structureIntégration des systèmes d'informationfr_FR
dc.subjectBusiness process model reuse fr_FR
dc.subjectUser business profileEn
dc.subjectBusiness process modelingEn
dc.subjectRecommender systemEn
dc.subjectBP model reuseEn
dc.titleSocial Business Process Model Recommender: An MDE approachfr_FR
dc.typeTechnical Report