Ontologies-Based Platform for Sociocultural Knowledge Management

International audienceIn this paper, we present a sociocultural platform aiming at persevering and capitalizing sociocul-tural events in Senegal. This platform relies on Semantic Web technologies. First, we discuss the two ontologies we provided to support our platform: an upper-level sociocultural ontology (USCO) and a human time ontol-ogy (HuTO). To build our upper-level ontology we proposed a methodology based on the theory of Russian psychologist Lev Vygotsky called "Vygotskian Framework". We also present how the upper-level ontology can be matched in the Linked Open Data (LOD) cloud. On the other hand, we present the Human Time Ontol-ogy (HuTO) of which major contributions are (i) the modeling of non-convex intervals (repetitive interval) like every Monday, (ii) representation deictic temporal expressions which form specific relations with time speech and (iii) qualitative temporal notions which are temporal notions relative to a culture or a geographical position. Finally, we discuss the platform designed on top of Semantic MediaWiki to apply our scientific contributions. indeed, the platform allows Senegalese communities to share and co-construct their sociocultural knowledge

HuTO: une Ontologie Temporelle Narrative pour les Applications du Web Sémantique: HuTO: une Ontologie Temporelle Narrative

National audienceThe temporal phenomena have many facets that are studied by different communities. In Semantic Web, large heterogeneous data are handled and produced. These data often have informal, semi-formal or formal temporal information which must be interpreted by software agents. In this paper we present Human Time Ontology (HuTO) an RDFS ontology to annotate and represent temporal data. A major contribution of HuTO is the modeling of non-convex intervals giving the ability to write queries for this kind of interval. HuTO also incorporates normalization and reasoning rules to explicit certain information. HuTO also proposes an approach which associates a temporal dimension to the knowledge base content. This facilitates information retrieval by considering or not the temporal aspect.Un défi majeur en informatique est la modélisation et le raisonnement sur les données temporelles. Ce travail est devenu encore plus important avec l'émergence du Web sémantique où de grandes quantités données hétérogènes sont manipulées. Ces données comportent souvent des informations temporelles informelles, semi-formelles ou formelles qui doivent être interprétées par les agents logiciels. Dans cet article nous présentons notre ontologie, Humain Time Ontologie (HuTO), une ontologie en RDFS pour annoter des ressources en RDF et représenter les expressions narratives temporelles. Une des contributions majeures de HuTO est la modélisation des intervalles non-convexes c'est-à-dire les intervalles répétitifs comme tous les mercredi mais également la possibilité d'écrire des requêtes sur ce type d'intervalle. HuTO intègre aussi des règles de normalisation et de raisonnement pour expliciter certaines informations temporelles. HuTO propose aussi une approche qui permet de garder distincte la dimension temporelle et les annotations du domaine métier. Cela facilite la recherche d'informations qu'elles soient temporelles ou non

A Learning Rate Analysis of Reinforcement Learning Algorithms in Finite-Horizon

Many reinforcement learning algorithms, like Q-Learning or R-Learning, correspond to adaptative methods for solving Markovian decision problems in infinite-horizon when no model is available. In this article we consider the particular framework of nonstationary finite-horizon Markov Decision Processes. After establishing a relationship between the finite-horizon total reward criterion and the average-reward criterion in finite-horizon, we define QH -Learning and RH -Learning for finite-horizon MDPs. Then we introduce the Ordinary Differential Equation (ODE) method to conduct a learning rate analysis of QH -Learning and RH - Learning. RH -Learning appears to be a version of QH -Learning with matrix-valued stepsizes, the corresponding gain matrix being very close to the optimal matrix which results from the ODE analysis. Experimental results confirm that performance hierarchy. 1 Introduction The search for optimal policies in Markov Decision Processes has been deeply studied according t..

Planning and monitoring of stored malting barley quality maintenance

Representing the stored grain ecosystem for quality maintenance implies therepresentation of all its characteristics that take part in the grain quality degradationprocess. A mixed qualitative and quantitative modelling is used to represent the storedgrain ecosystem. The temperature, moisture content and presence of insects are used ascontrol variables. The quality maintenance operations are represented as actions to beexecuted in time requiring available equipment and consumable. Our planningapproach involves three consecutive stages: treatment to obtain a safe grain storagecondition, storage to maintain the storage condition and dispatch to respond to themarket requirements

Sociocultural Ontology: Upper-level and Domain Ontologies

National audienc