Search results for "Semantic Web."
showing 9 items of 129 documents
Dynamic, Behavior-Based User Profiling Using Semantic Web Technologies in a Big Data Context
2013
pp. 363-372; International audience; The success of shaping the e-society is crucially dependent on how well technology adapts to the needs of each single user. A thorough understanding of one's personality, interests, and social connections facilitate the integration of ICT solutions into one's everyday life. The MindMinings project aims to build an advanced user profile, based on the automatic processing of a user's navigation traces on the Web. Given the various needs underpinned by our goal (e.g. integration of heterogeneous sources and automatic content extraction), we have selected Semantic Web technologies for their capacity to deliver machine-processable information. Indeed, we have…
A web search methodology for different user typologies
2009
Search engines and directories are the main tools used to find desired information into the ocean of digital contents that is the Web. However, they are not presently able to understand the user specific needs and starting knowledge because their inability to simulate the processes of human mind. Natural Language Processing, Folksonomy, Semantic Web and Serendipitous Surfing are some of the recent research fields towards understanding of human natural language and in general of real user needs. This work aims to add one step more to this evolution path by presenting a new search methodology that allows users to create new knowledge paths on the web based on their specific requirements. Thus…
Informal learning through expertise mining in the social web
2012
The advent of Web 2.0, also called the Social Web, has changed the way people interact with the Web. Assisted by the technologies associated with this new trend, users now play a much more active role as content providers. This Web paradigm shift has also changed how companies operate and interact with their employees, partners and customers. The challenge for companies and research institutions is now to develop semi-automated tools for gathering usable and explicit knowledge from such content. With the aim of facilitating the achievement of such a challenge, in this work a platform architecture for informal learning, which is based on semantic technologies, is proposed. Such platform perm…
Explainable AI for Industry 4.0 : Semantic Representation of Deep Learning Models
2022
Artificial Intelligence is an important asset of Industry 4.0. Current discoveries within machine learning and particularly in deep learning enable qualitative change within the industrial processes, applications, systems and products. However, there is an important challenge related to explainability of (and, therefore, trust to) the decisions made by the deep learning models (aka black-boxes) and their poor capacity for being integrated with each other. Explainable artificial intelligence is needed instead but without loss of effectiveness of the deep learning models. In this paper we present the transformation technique between black-box models and explainable (as well as interoperable) …
An Automatic Ontology-Based Approach to Support Logical Representation of Observable and Measurable Data for Healthy Lifestyle Management: Proof-of-C…
2020
Background Lifestyle diseases, because of adverse health behavior, are the foremost cause of death worldwide. An eCoach system may encourage individuals to lead a healthy lifestyle with early health risk prediction, personalized recommendation generation, and goal evaluation. Such an eCoach system needs to collect and transform distributed heterogenous health and wellness data into meaningful information to train an artificially intelligent health risk prediction model. However, it may produce a data compatibility dilemma. Our proposed eHealth ontology can increase interoperability between different heterogeneous networks, provide situation awareness, help in data integration, and discover…
Context-Aware Adaptive System For M- Learning Personalization
2014
International audience; Context-aware mobile learning is becoming important because of the dynamic and continually changing learning settings in learner's mobile environment, giving rise to many different learning contexts that are difficult to apprehend. To provide personalization of learning content, we aim to develop a recommender system based on semantic modeling of learning contents and learning context. This modeling is complemented by a behavioral part made up of rules and metaheuristics used to optimize the combination of pieces of learning contents according to learner's context. All these elements form a new approach to mobile learning.
Cognitive Linguistics as the Underlying Framework for Semantic Annotation
2012
In recent years many attempts have been made to design suitable sets of rules aimed at extracting the semantic meaning from plain text, and to achieve annotation, but very few approaches make extensive use of grammars. Current systems are mainly focused on extracting the semantic role of the entities described in the text. This approach has limitations: in such applications the semantic role is conceived merely as the meaning of the involved entities without considering their context. As an example, current semantic annotators often specify a date entity without any annotation regarding the kind of the date itself i.e. a birth date, a book publication date, and so on. Moreover, these system…
Vers une plateforme sémantique pour l'enseignement des sciences et de la culture numérique
2016
The technologies of Semantic Web for education have several advantages: accessibility and sustainability of resources, increased clarification and organization. Here we present our project of a semantic platform, the interest of those technologies, and a human / machine communication model that helps learner, teacher and scientist to think better, reflexively, the activities of each of them. The experiments about digital culture pave the way for a quality digital training.
GUI personalization framework driven by personal semantic user profile
2017
Sovelluskehys käyttöliittymän personointiin käyttäen semanttista käyttäjäprofiilia. Internetin kehittyessä maailma verkostoituu yhä enemmän. Käytämme päivittäin monia laitteita ja erilaisia käyttöliittymiä, mutta vaikka ne monesti jakavat yleisiä käytänteitä ja kuvakkeita, eivät ne kuitenkaan mukaudu yksittäisen käyttäjän tarpeisiin. Vaikka ihmisillä on monia eri ominaisuuksia tai rajoitteita, jotka vaikeuttavat käyttöliittymän omaksumista, palvelun tai ohjelman näkökulmasta käyttäjät mielletään silti yhtenä homogeenisenä joukkona, jonka on mukauduttava käyttöliittymään. Omaksumiskykyyn vaikuttavia tekijöitä ovat esimerkiksi kieli, ikä, koulutustausta ja kulttuuri. Mukautuvan käyttöliittymä…