ENABLING COLLABORATIVE E-HEALTH THROUGH TRIPLESPACE COMPUTING

Abstract The design and promotion of electronic patient summaries as an instrument to facilitate the pervasive delivery of healthcare is emerging as a key technology in eHealth solutions. From the technical point of view this requires powerful middleware systems supporting interoperability, multi-lingualism, security and patient privacy. In this paper we present a semantic coordination model and describe how it can be used to support pervasive access to electronic patient summaries

Automatic Expansion of Domain-Specific Affective Models for Web Intelligence Applications

Sentic computing relies on well-defined affective models of different complexity - polarity to distinguish positive and negative sentiment, for example, or more nuanced models to capture expressions of human emotions. When used to measure communication success, even the most granular affective model combined with sophisticated machine learning approaches may not fully capture an organisation's strategic positioning goals. Such goals often deviate from the assumptions of standardised affective models. While certain emotions such as Joy and Trust typically represent desirable brand associations, specific communication goals formulated by marketing professionals often go beyond such standard dimensions. For instance, the brand manager of a television show may consider fear or sadness to be desired emotions for its audience. This article introduces expansion techniques for affective models, combining common and commonsense knowledge available in knowledge graphs with language models and affective reasoning, improving coverage and consistency as well as supporting domain-specific interpretations of emotions. An extensive evaluation compares the performance of different expansion techniques: (i) a quantitative evaluation based on the revisited Hourglass of Emotions model to assess performance on complex models that cover multiple affective categories, using manually compiled gold standard data, and (ii) a qualitative evaluation of a domain-specific affective model for television programme brands. The results of these evaluations demonstrate that the introduced techniques support a variety of embeddings and pre-trained models. The paper concludes with a discussion on applying this approach to other scenarios where affective model resources are scarce

The Industry Challenges The Research.

Abstract. Semantic Web technology is being increasingly applied in a large spectrum of applications in which domain knowledge is conceptualized and formalized (e.g., by means of an ontology) in order to support diversified knowledge processing (e.g., reasoning) by machine. Moreover, through the subtle joining of (cognitive) human reasoning and (logical) machine reasoning, it is possible for humans and machines to share complementary tasks. Some examples of application areas where these tasks arise are: corporate portals and knowledge management, e-commerce, e-work, healthcare, e-government, natural language understanding and automated translation, information search, data and services integration, social networks and collaborative filtering, knowledge mining, and so on. From a social and economic perspective, this emerging technology should contribute to growth in economic wealth, but it must also show clear cut value for everyday activities through technological transparency and efficiency. The uptake of Semantic Web technology by industry is progressing slowly. One of the problems is that academia is not always awar

Makna and MultiMakna: towards semantic and multimedia capability in wikis for the emerging web

The merging of Wikis and the Semantic Web leads to the possibility of editable Web pages where users can create, change and store knowledge. This generated knowledge is usable to enhance the way conventional Wikis organize, retrieve and present content. However, Web-based information is increasingly non-textual. While semantic Wikis are expected to provide a powerful path to the public Semantic Web, multimedia content support is already poor in their non-semantic counterparts. This paper approaches how collaborative multimedia information management can be realised by unifying principles from Wiki, Semantic Web and multimedia research. As a result we introduce the Makna semantic Wiki and propose an extension to integrate multimedia support, entitled MultiMakna

Abstract

One of the main items on the eHealth agenda of the European Community is the design and promotion of electronic patient summaries as an instrument to facilitate the pervasive delivery of healthcare, thus ensuring the right to patient mobility and increasing the productivity and quality of health service delivery. From a technical point of view this objective requires middleware technology which is able to cope with the stringent interoperability, multi-lingualism, security and privacy requirements arising in eHealth settings. In this paper we present triplespace computing, a coordination middleware for the Semantic Web and demonstrate its relevance to the realization of the European patient summary infrastructure. 1