#eswc2014 Accepted Posters and Demos published: FIVE LinkedTV submissions will be shown!

The full list of Posters and Demos to be shown next Thursday at ESWC2014 has been published, and LinkedTV is proud to note that no less than FIVE submissions from the project will be shown there!

We present an approach that leverages on the knowledge present on the Web for identifying and enriching relevant items inside a News video and displaying them in a timely and user friendly fashion. This second screen prototype (i) collects and o ffers information about persons, locations, organizations and concepts occurring in the newscast, and (ii) combines them for enriching the underlying story along fi ve main dimensions: expert’s opinions, timeline, in depth, in other sources, and geo-localized comments from other viewers. Starting from preliminary insights coming from the named entities spotted on the subtitles, we expand this initial context to a broader event representation by relying in the knowledge of other Web documents talking about the same fact. An online demo of the proposed solution is available at http://linkedtv.project.cwi.nl/news/

Entities play a key role in knowledge bases in general and in the Web of Data in particular. Entities are generally described with a lot of properties, this is the case for DBpedia. It is, however, difficult to assess which ones are more important than others for particular tasks such as visualizing the key facts of an entity or fi ltering out the ones which will yield better instance matching. In this paper, we perform a reverse engineering of the Google Knowledge graph panel to find out what are the most important properties for an entity according to Google. We compare these results with a survey we conducted on 152 users. We fi nally show how we can represent and explicit this knowledge using the Fresnel vocabulary.

In this paper we present LiFR, a lightweight DL reasoner capable of performing in resource-constrained devices, that implements a fuzzy extension of Description Logic Programs. Preliminary evaluation against two existing fuzzy DL reasoners and within a real-world use case has shown promising results.

This paper introduces the LinkedTV User Model Ontology (LUMO), developed within the LinkedTV EU project. LUMO aims to semantically represent user-pertinent information in the networked media domain and to enable personalisation and contextualisation of concepts and content via semantic reasoning. The design principles of LUMO and its connection to relevant ontologies and known vocabularies is described.

Increasingly, European citizens consume television content together with devices connected to the Internet where they can look up related information. In parallel, growing amounts of Linked Open Data are being published on the Web, including rich metadata about its cultural heritage. Linked Data and semantic technologies could enable broadcasters to achieve added value for their content at low cost through the re-use of existing and extracted metadata. We present on-going work in the LinkedTV project, whose goal is to achieve seamless interlinking between TV and Web content on the basis of semantic annotations: two scenarios validated by user trials – Linked News and the Hyperlinked Documentary – and a companion screen application which provides related information for those programs during viewing.

Join the session Thursday morning at ESWC, and if you can’t be there, follow Twitter @linkedtv and check news at linkedtv.eu for updates from the conference!


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