Equal Time for Data on the Internet with WebSemantics

Projet RODINRésumé disponible dans le fichier PD

MLEA: a solution for users of android in UTP Virtual

This paper describes a design of an educational platform for a mobile learning architecture, which is a state of the art topic in distance education. The product will allow users to interact in an efficient, flexible, and transparent fashion with a web-based education environment, in this case Module Object-Oriented Dynamic Learning Environment (Moodle), using Android mobile devices. In order to provide a strong and lasting architecture, the Service Oriented Architecture (SOA) methodology is used given that it allows easy software re-utilization as well as integration of heterogeneous services. The architecture is based on web services implemented with Representational State Transfer (REST), as it has been demonstrated to be lighter and less consuming than other protocols, for devices with limited resources such as mobile devices. Web services provide the communication means between the server side and the client side of the architecture, whereas agents are used to deliver the services itself. The authors propose the development of an environment that facilitates the integration of various educational resources to support m-learning. An important aspect of the proposal is the offering of a tool to provide customized alerts for students and teachers, enabling them to remain updated about activities taking place in the coursesThis paper describes a design of an educational platform for a mobile learning architecture, which is a state of the art topic in distance education. The product will allow users to interact in an efficient, flexible, and transparent fashion with a web-based education environment, in this case Module Object-Oriented Dynamic Learning Environment (Moodle), using Android mobile devices. In order to provide a strong and lasting architecture, the Service Oriented Architecture (SOA) methodology is used given that it allows easy software re-utilization as well as integration of heterogeneous services. The architecture is based on web services implemented with Representational State Transfer (REST), as it has been demonstrated to be lighter and less consuming than other protocols, for devices with limited resources such as mobile devices. Web services provide the communication means between the server side and the client side of the architecture, whereas agents are used to deliver the services itself. The authors propose the development of an environment that facilitates the integration of various educational resources to support m-learning. An important aspect of the proposal is the offering of a tool to provide customized alerts for students and teachers, enabling them to remain updated about activities taking place in the course

In the quest of specific-domain ontology components for the semantic web

This paper describes an approach we have been using to identify specific-domain ontology components by using Self-Organizing Maps. These components are clustered together in a natural way according to their similarity. The knowledge maps, as we call them, show colored regions containing knowledge components that may be used to populate an specific-domain ontology. Later, these ontology may be used by software agents to carry out basic reasoning task on our behalf. In particular, we deal with the issue of not constructing the ontology from scratch, our approach helps us to speed up the ontology creation process

User preferences in intelligent environments

Intelligent Environments and other Computer Science sub-fields based on the concepts of context and context-awareness are created with the explicit or implicit intention of providing services which are satisfying to the intended users of those environments. This article discusses the pragmatic importance of Preferences within the process of developing Intelligent Environments as a conceptual tool to achieve that system-user alignment and we also look at the practical challenges of implementing different aspects of the concept of Preferences. This study is not aimed at providing a definitive solution, rather to assess the advantages and disadvantages of different available options with the view to inform the next wave of developments in the area

Named Entity Extraction for Knowledge Graphs: A Literature Overview

An enormous amount of digital information is expressed as natural-language (NL) text that is not easily processable by computers. Knowledge Graphs (KG) offer a widely used format for representing information in computer-processable form. Natural Language Processing (NLP) is therefore needed for mining (or lifting) knowledge graphs from NL texts. A central part of the problem is to extract the named entities in the text. The paper presents an overview of recent advances in this area, covering: Named Entity Recognition (NER), Named Entity Disambiguation (NED), and Named Entity Linking (NEL). We comment that many approaches to NED and NEL are based on older approaches to NER and need to leverage the outputs of state-of-the-art NER systems. There is also a need for standard methods to evaluate and compare named-entity extraction approaches. We observe that NEL has recently moved from being stepwise and isolated into an integrated process along two dimensions: the first is that previously sequential steps are now being integrated into end-to-end processes, and the second is that entities that were previously analysed in isolation are now being lifted in each other's context. The current culmination of these trends are the deep-learning approaches that have recently reported promising results.publishedVersio

Peer-to-peer systems for simple and flexible information sharing

Includes abstract.Includes bibliographical references (leaves 76-80).Peer to peer computing (P2P) is an architecture that enables applications to access shared resources, with peers having similar capabilities and responsibilities. The ubiquity of P2P computing and its increasing adoption for a decentralized data sharing mechanism have fueled my research interests. P2P networks are useful for sharing content files containing audio, video, and data. This research aims to address the problem of simple and flexible access to data from a variety of data sources across peers with different operating systems, databases and hardware. The proposed architecture makes use of SQL queries, web services, heterogeneous database servers and XML data transformation for the peer to peer data sharing prototype. SQL queries and web services provide a data sharing mechanism that allows both simple and flexible data access

In the quest of specific-domain ontology components for the semantic web

This paper describes an approach we have been using to identify specific-domain ontology components by using Self-Organizing Maps. These components are clustered together in a natural way according to their similarity. The knowledge maps, as we call them, show colored regions containing knowledge components that may be used to populate an specific-domain ontology. Later, these ontology may be used by software agents to carry out basic reasoning task on our behalf. In particular, we deal with the issue of not constructing the ontology from scratch, our approach helps us to speed up the ontology creation process

Ontology-Based Framework for the Automatic Recognition of Activities of Daily Living Using Class Expression Learning Techniques

The miniaturization and price reduction of sensors have encouraged the proliferation of smart environments, in which multitudinous sensors detect and describe the activities carried out by inhabitants. In this context, the recognition of activities of daily living has represented one of the most developed research areas in recent years. Its objective is to determine what daily activity is developed by the inhabitants of a smart environment. In this field, many proposals have been presented in the literature, many of them being based on ad hoc ontologies to formalize logical rules, which hinders their reuse in other contexts. In this work, we propose the use of class expression learning (CEL), an ontology-based data mining technique, for the recognition of ADL. This technique is based on combining the entities in the ontology, trying to find the expressions that best describe those activities. As far as we know, it is the first time that this technique is applied to this problem. To evaluate the performance of CEL for the automatic recognition of activities, we have first developed a framework that is able to convert many of the available datasets to all the ontology models we have found in the literature for dealing with ADL. Two different CEL algorithms have been employed for the recognition of eighteen activities in two different datasets. Although all the available ontologies in the literature are focused on the description of the context of the activities, the results show that the sequence of the events produced by the sensors is more relevant for their automatic recognition, in general terms