Semantic Characterization of Context of Use and Contents for User-Centric Media Retrieval

When users access online media, they need and desire to get an experience tailored to their specific, personal context and situation. This is becoming more and more relevant with the ever-increasing amount of available contents users may choose from. In order to provide user-centric functionalities (such as relevant searches, content adaptation, customization and recommendation), both the annotation of contents with semantically rich metadata and an accurate model of the individual users and their respective contexts of use are needed. In this context, we propose a solution to automatically characterize both the context of use and the contents. It provides dynamic, adaptive user models, with explicit and implicit information; as well as content descriptors that may be later used to match the most suitable contents for each user. Users always keep a pivotal role throughout the whole process: providing new contents, contributing to moderated folks onomies, overseeing their own user model, etc

A Metadata-Enabled Scientific Discourse Platform

Scientific papers and scientific conferences are still, despite the emergence of several new dissemination technologies, the de-facto standard in which scientific knowledge is consumed and discussed. While there is no shortage of services and platforms that aid this process (e.g. scholarly search engines, websites, blogs, conference management programs), a widely accepted platform used to capture and enrich the interactions of research community has yet to appear. As such, we aim to create new ways for the members and interested people working in research communities to interact; before, during and after their conferences. Furthermore, to serve as a base to these interactions, we want not only to obtain, format and manage a body of legacy and new papers related to this community but also to aggregate several useful information and services to the environment of a discourse platform

Approaches to Semantic Web Services: An Overview and Comparison

Abstract. The next Web generation promises to deliver Semantic Web Services (SWS); services that are self-described and amenable to automated discovery, composition and invocation. A prerequisite to this, however, is the emergence and evolution of the Semantic Web, which provides the infrastructure for the semantic interoperability of Web Services. Web Services will be augmented with rich formal descriptions of their capabilities, such that they can be utilized by applications or other services without human assistance or highly constrained agreements on interfaces or protocols. Thus, Semantic Web Services have the potential to change the way knowledge and business services are consumed and provided on the Web. In this paper, we survey the state of the art of current enabling technologies for Semantic Web Services. In addition, we characterize the infrastructure of Semantic Web Services along three orthogonal dimensions: activities, architecture and service ontology. Further, we examine and contrast three current approaches to SWS according to the proposed dimensions

Semantic Web Services Provisioning

Semantic Web Services constitute an important research area, where vari ous underlying frameworks, such as WSMO and OWL-S, define Semantic Web ontologies to describe Web services, so they can be automatically discovered, composed, and invoked. Service discovery has been traditionally interpreted as a functional filter in current Semantic Web Services frameworks, frequently performed by Description Logics reasoners. However, semantic provisioning has to be performed taking Quality-of-Service (QOS) into account, defining user preferences that enable QOS-aware Semantic Web Service selection. Nowadays, the research focus is actually on QOS-aware processes, so cur rent proposals are developing the field by providing QOS support to semantic provisioning, especially in selection processes. These processes lead to opti mization problems, where the best service among a set of services has to be selected, so Description Logics cannot be used in this context. Furthermore, user preferences has to be semantically defined so they can be used within selection processes. There are several proposals that extend Semantic Web Services frameworks allowing QOS-aware semantic provisioning. However, proposed selection techniques are very coupled with their proposed extensions, most of them being implemented ad hoc. Thus, there is a semantic gap between functional descriptions (usually using WSMO or OWL-S) and user preferences, which are specific for each proposal, using different ontologies or even non-semantic de scriptions, and depending on its corresponding ad hoc selection technique. In this report, we give an overview of most important Semantic Web Ser vices frameworks, showing a comparison between them. Then, a thorough analysis of state-of-the art proposals on QOS-aware semantic provisioning and user preferences descriptions is presented, discussing about their applicabil ity, advantages, and defects. Results from this analysis motivate our research work, which has been already materialized in two early contributions.Los servicios web semánticos constituyen un importante campo de inves tigación, en el cual distintos frameworks, como por ejemplo WSMO y OWL-S, definen ontologías de la web semántica para describir servicios web, de for ma que estos puedan ser descubiertos, compuestos e invocados de manera automática. El descubrimiento de servicios ha sido interpretado tradicional mente como un filtro funcional en los frameworks actuales de servicios web semánticos, usando para ello razonadores de lógica descriptiva. Sin embargo, las tareas de aprovisionamiento semántico deberían tener en cuenta la calidad del servicio, definiendo para ello preferencias de usuario de manera que sea posible realizar una selección de servicios web semánticos sensible a la cali dad. Actualmente, el foco de la investigación está en procesos sensibles a la ca lidad, por lo que las propuestas actuales están trabajando en este campo intro duciendo el soporte adecuado a la calidad del servicio dentro del aprovisio namiento semántico, y principalmente en las tareas de selección. Estas tareas desembocan en problemas de optimización, donde el mejor servicio de entre un concjunto debe ser seleccionado, por lo que las lógicas descriptivas no pue den ser usadas en este contexto. Además, las preferencias de usuario deben ser definidas semánticamente, de forma que puedan ser usadas en las tareas de selección. Existen bastantes propuestas que extienden los frameworks de servicios web semánticos para habilitar el aprovisionamiento sensible a la calidad. Sin embargo, las técnicas de selección propuestas están altamente acopladas con dichas extensiones, donde la mayoría de ellas implementan algoritmos ad hoc. Por tanto, existe un salto semántico entre las descripciones funcionales (nor malmente usando WSMO o OWL-S) y las preferencias de usuario, las cuales son definidas específicamente por cada propuesta, usando ontologías distin tas o incluso descripciones no semánticas que dependen de la correspondiente técnica de selección ad hoc

An Ontology Based Approach Towards A Universal Description Framework for Home Networks

Current home networks typically involve two or more machines sharing network resources. The vision for the home network has grown from a simple computer network, to every day appliances embedded with network capabilities. In this environment devices and services within the home can interoperate, regardless of protocol or platform. Network clients can discover required resources by performing network discovery over component descriptions. Common approaches to this discovery process involve simple matching of keywords or attribute/value pairings. Interest emerging from the Semantic Web community has led to ontology languages being applied to network domains, providing a logical and semantically rich approach to both describing and discovering network components. In much of the existing work within this domain, developers have focused on defining new description frameworks in isolation from existing protocol frameworks and vocabularies. This work proposes an ontology-based description framework which takes the ontology approach to the next step, where existing description frameworks are in- corporated into the ontology-based framework, allowing discovery mechanisms to cover multiple existing domains. In this manner, existing protocols and networking approaches can participate in semantically-rich discovery processes. This framework also includes a system architecture developed for the purpose of reconciling existing home network solutions with the ontology-based discovery process. This work also describes an implementation of the approach and is deployed within a home-network environment. This implementation involves existing home networking frameworks, protocols and components, allowing the claims of this work to be examined and evaluated from a ‘real-world’ perspective

Adaptive intelligent personalised learning (AIPL) environment

As individuals the ideal learning scenario would be a learning environment tailored just for how we like to learn, personalised to our requirements. This has previously been almost inconceivable given the complexities of learning, the constraints within the environments in which we teach, and the need for global repositories of knowledge to facilitate this process. Whilst it is still not necessarily achievable in its full sense this research project represents a path towards this ideal.In this thesis, findings from research into the development of a model (the Adaptive Intelligent Personalised Learning (AIPL)), the creation of a prototype implementation of a system designed around this model (the AIPL environment) and the construction of a suite of intelligent algorithms (Personalised Adaptive Filtering System (PAFS)) for personalised learning are presented and evaluated. A mixed methods approach is used in the evaluation of the AIPL environment. The AIPL model is built on the premise of an ideal system being one which does not just consider the individual but also considers groupings of likeminded individuals and their power to influence learner choice. The results show that: (1) There is a positive correlation for using group-learning-paradigms. (2) Using personalisation as a learning aid can help to facilitate individual learning and encourage learning on-line. (3) Using learning styles as a way of identifying and categorising the individuals can improve their on-line learning experience. (4) Using Adaptive Information Retrieval techniques linked to group-learning-paradigms can reduce and improve the problem of mis-matching. A number of approaches for further work to extend and expand upon the work presented are highlighted at the end of the Thesis

An Analysis of Service Ontologies

Services are increasingly shaping the world’s economic activity. Service provision and consumption have been profiting from advances in ICT, but the decentralization and heterogeneity of the involved service entities still pose engineering challenges. One of these challenges is to achieve semantic interoperability among these autonomous entities. Semantic web technology aims at addressing this challenge on a large scale, and has matured over the last years. This is evident from the various efforts reported in the literature in which service knowledge is represented in terms of ontologies developed either in individual research projects or in standardization bodies. This paper aims at analyzing the most relevant service ontologies available today for their suitability to cope with the service semantic interoperability challenge. We take the vision of the Internet of Services (IoS) as our motivation to identify the requirements for service ontologies. We adopt a formal approach to ontology design and evaluation in our analysis. We start by defining informal competency questions derived from a motivating scenario, and we identify relevant concepts and properties in service ontologies that match the formal ontological representation of these questions. We analyze the service ontologies with our concepts and questions, so that each ontology is positioned and evaluated according to its utility. The gaps we identify as the result of our analysis provide an indication of open challenges and future work