Deliverable D7.5 LinkedTV Dissemination and Standardisation Report v2

This deliverable presents the LinkedTV dissemination and standardisation report for the project period of months 19 to 30 (April 2013 to March 2014)

Deliverable D9.3 Final Project Report

This document comprises the final report of LinkedTV. It includes a publishable summary, a plan for use and dissemination of foreground and a report covering the wider societal implications of the project in the form of a questionnaire

Deliverable D7.3 LinkedTV Dissemination and Standardisation Report v1

This deliverable presents the LinkedTV dissemination and standardisation report for the first 18 months of the project

Social Event Detection at MediaEval: a three-year retrospect of tasks and results

Petkos G, Papadopoulos S, Mezaris V, et al. Social Event Detection at MediaEval: a three-year retrospect of tasks and results. In: Proc. ACM ICMR 2014 Workshop on Social Events in Web Multimedia (SEWM). 2014.This paper presents an overview of the Social Event Detection (SED) task that has been running as part of the MediaEval benchmarking activity for three consecutive years (2011 - 2013). The task has focused on various aspects of social event detection and retrieval and has attracted a significant number of participants. We discuss the evolution of the task and the datasets, we summarize the set of approaches ursued by participants and evaluate the overall collective progress that has been achieved

Deliverable D7.7 Dissemination and Standardisation Report v3

This deliverable presents the LinkedTV dissemination and standardisation report for the project period of months 31 to 42 (April 2014 to March 2015)

Deliverable D2.7 Final Linked Media Layer and Evaluation

This deliverable presents the evaluation of content annotation and content enrichment systems that are part of the final tool set developed within the LinkedTV consortium. The evaluations were performed on both the Linked News and Linked Culture trial content, as well as on other content annotated for this purpose. The evaluation spans three languages: German (Linked News), Dutch (Linked Culture) and English. Selected algorithms and tools were also subject to benchmarking in two international contests: MediaEval 2014 and TAC’14. Additionally, the Microposts 2015 NEEL Challenge is being organized with the support of LinkedTV

Deliverable D2.6 LinkedTV Framework for Generating Video Enrichments with Annotations

This deliverable describes the final LinkedTV framework that provides a set of possible enrichment resources for seed video content using techniques such as text and web mining, information extraction and information retrieval technologies. The enrichment content is obtained from four type of sources: a) by crawling and indexing web sites described in a white list specified by the content partners, b) by querying the API or SPARQL endpoint of the Europeana digital library network which is publicly exposed, c) by querying multiple social networking APIs, d) by hyperlinking to other parts of TV programs within the same collection using a Solr index. This deliverable also describes an additional content annotation functionality, namely labelling enrichment (as well as seed) content with thematic topics, as well as the process of exposing content annotations to this module and to the filtering services of LinkedTV’s personalization workflow. We illustrate the enrichment workflow for the two main scenarios of LinkedTV which have lead to the development of the LinkedCulture and LinkedNews applications, which respectively use the TVEnricher and TVNewsEnricher enrichment services. The original title of this deliverable from the DoW was Advanced concept labelling by complementary Web mining

Deliverable D7.8 Newsletter

This deliverable provides the first year newsletter of the LinkedTV project

Deliverable D2.4 Annotation and retrieval module of media fragments

This deliverable presents an update of the LinkedTV metadata model as part of the WP2 of the LinkedTV project. It includes a set of mappings with other ontologies such as LUMO used in WP4. Second, we describe the converter module named TV2RDF, implemented as a REST service, that populates the LinkedTV triple store with RDF data resulting from the automatic conversion of legacy metadata provided by the content provider, of automatic analysis results generated by WP1, and of named entity recognition and disambiguation applied on subtitles provided with the content. Third, we describe the model and the service that aims to provide enrichments for particular media fragments of a seed video content. Finally, we present a number of useful SPARQL queries that are typically needed by the LinkedTV player or other clients that wish to reuse this semantic dataset