Cognitive Approach to e-Learning in Sciences and Technologies

This article describes the approach adopted and the results obtained by the international team developing WBLST (Web Based Learning in Sciences and Technologies) a Web-based application for e-learning, developed for the students of “UVPL: Université Virtuelle des Pays de la Loire”. The developed e-learning system covers three levels of learning activities - content, exercises, and laboratory. The delivery model is designed to operate with domain concepts as relevant providers of semantic links. The aim is to facilitate the overview and to help the establishment of a mental map of the learning material. The implemented system is strongly based on the organization of the instruction in virtual classes. The obtained quality of the system is evaluated on the bases of feedback form students and professors

An Efficient Architecture for Information Retrieval in P2P Context Using Hypergraph

Peer-to-peer (P2P) Data-sharing systems now generate a significant portion of Internet traffic. P2P systems have emerged as an accepted way to share enormous volumes of data. Needs for widely distributed information systems supporting virtual organizations have given rise to a new category of P2P systems called schema-based. In such systems each peer is a database management system in itself, ex-posing its own schema. In such a setting, the main objective is the efficient search across peer databases by processing each incoming query without overly consuming bandwidth. The usability of these systems depends on successful techniques to find and retrieve data; however, efficient and effective routing of content-based queries is an emerging problem in P2P networks. This work was attended as an attempt to motivate the use of mining algorithms in the P2P context may improve the significantly the efficiency of such methods. Our proposed method based respectively on combination of clustering with hypergraphs. We use ECCLAT to build approximate clustering and discovering meaningful clusters with slight overlapping. We use an algorithm MTMINER to extract all minimal transversals of a hypergraph (clusters) for query routing. The set of clusters improves the robustness in queries routing mechanism and scalability in P2P Network. We compare the performance of our method with the baseline one considering the queries routing problem. Our experimental results prove that our proposed methods generate impressive levels of performance and scalability with with respect to important criteria such as response time, precision and recall.Comment: 2o pages, 8 figure

Semantic reconciliation in peer multi-data source management system

International audienceIn Peer Data Management system (PDMS), two fundamental problems for data fusion arise: (a) how to build a semantic reconciliation between data sources schemas managed by peers, and (b) how to locate relevant peers for a given query. Our proposal lies in the application of multi-data source fusion approach [15] in the PDMS context. Multi-data source schemas, which are distributed shared and maintained by peers, are the basis of a semantic overlay network. The design for Peer Multi-Data source Management System (PMDMS) was presented in [16] is an extension of MDS-Manager system [14] [15] where data sources are distributed among peers. In this paper, we focus on the MatchMaker component in PMDMS that has the semantic reconciliation (i.e. mapping) responsibility between concrete data sources schemas (i.e. schemas describing data to share with other peers) also known as expertise. Our approach of semantic reconciliation is based on ontologies and XML technologies. Indeed, the peer schema (i.e. an ontology expressed with OWL/RDF), is annotated with a set of synonymous in order to guide later the search of semantics equivalences between expertises. The mappings results are stored in an XML document called Conflicts data source (a part of the multi-data source) as semantic links between concepts such as equivalence, synonym, homonym or disjoint concepts

Multi-Data Source Fusion in PDMS

Abstract. In this paper, we propose a new approach for data fusion in the context of schema-based Peer-To-Peer (P2P) systems. Schema-based systems manage and provide query capabilities for (semi-)structured information: queries have to be formulated in terms of schema. The dominating schema-based systems are relational databases or XML documents. Schema-based P2P are called Peer Data Management system (PDMS). A challenging problem in a schema-based peer-to-peer (P2P) system is how to locate peers that are relevant with respect to a given query. Our proposal, lies in application of the multi-data source fusion approach [17] in the context of PDMS. In this context, a multi-data source schema describes static or active data sources (in addition of their conflicts) shared by peers which are semantically neighbors. Static data sources can be structured or semi-structured (e.g. relational databases or XML documents), whereas active sources are services (e.g. Java Applications, Web Services etc.). Multi-data source schemas, distributed, shared and maintained by peers, are the basis of a semantic overlay network. This network and the power of Multi-data source Fusion Language (MFL) [17] are exploited, in this paper, for efficient query propagation towards the relevant peers. The design of our proposed system is, an extension of MDSManager [16][17], called Peer Multi-Data source Management System (PMDMS). We give a performance evaluation of the semantic query routing with respect to important criteria such as precision, recall, response time and number of messages. We compare next this result with the routing algorithm of SenPeer [4], a PDMS developed recently with respect to an hybrid (i.e. super-peer/peer) approach where peers are connected to superpeers according to their semantic domains. Our proposal compared to an hybrid approach shows a better performance regarding the precision, the response time and the number of messages exchanged between peers.

Multi-data source fusion

International audienceThis paper describes a new approach of heterogeneous data source fusion. Data sources are either static or active: static data sources can be structured or semi-structured, whereas active sources are services. In order to develop data sources fusion systems in dynamic contexts, we need to study all issues raised by the matching paradigms. This challenging problem becomes crucial with the dominating role of the internet. Classical approaches of data integration, based on schemas mediation, are not suitable to the World Wide Web (WWW) environment where data is frequently modified or deleted. Therefore, we develop a loosely integrated approach that takes into consideration both conflict management and semantic rules which must be enriched in order to integrate new data sources. Moreover, we introduce an XML-based Multi-data source Fusion Language (MFL) that aims to define and retrieve conflicting data from multiple data sources. The system, which is developed according to this approach, is called MDSManager (Multi-Data Source Manager). The benefit of the proposed framework is shown through a real world application based on web data sources fusion which is dedicated to online markets indices tracking. Finally, we give an evaluation of our MFL language. The results show that our language improves significantly the XQuery language especially considering its expressiveness power and its performances

MashUp web data sources and services based on semantic queries

International audienceThis paper describes a process for mashing heterogeneous data sources based on the Multi-data source Fusion Approach (MFA) (Nachouki and Quafafou, 2008 [52]). The aim of MFA is to facilitate the fusion of heterogeneous data sources in dynamic contexts such as the Web. Data sources are either static or active: static data sources can be structured or semi-structured (e.g. XML documents or databases), whereas active sources are services (e.g. Web services). Our main objective is to combine (Web) data sources with a minimal effort required from the user. This objective is crucial because the mashing process implies easy and fast integration of data sources. We suppose that the user is not expert in this field but he/she understands the meaning of data being integrated. In this paper, we consider two important aspects of the Web mashing process. The first one concerns the information extraction from the Web. The results of this process are the static data sources that are used later together with services in order to create a new result/application. The second one concerns the problem of semantic reconciliation of data sources. This step consists to generate the Conflicts data source in order to improve the problem of rewriting semantic queries into sub-queries (not addressed in this paper) over data sources. We give the design of our system MDSManager. We show this process through a real-life application

USING SEMANTICS EQUIVALENCES FOR MRL QUERIES REWRITING IN MULTI-DATA SOURCE FUSION SYSTEMS

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