Creating enriched YouTube media fragments With NERD using timed-text

This demo enables the automatic creation of semantically annotated YouTube media fragments. A video is first ingested in the Synote system and a new method enables to retrieve its associated subtitles or closed captions. Next, NERD is used to extract named entities from the transcripts which are then temporally aligned with the video. The entities are disambiguated in the LOD cloud and a user interface enables to browse through the entities detected in a video or get more information. We evaluated our application with 60 videos from 3 YouTube channels

STEM: stacked threshold-based entity matching for knowledge base generation

One of the major issues encountered in the generation of knowledge bases is the integration of data coming from a collection of heterogeneous data sources. A key essential task when integrating data instances is the entity matching. Entity matching is based on the definition of a similarity measure among entities and on the classification of the entity pair as a match if the similarity exceeds a certain threshold. This parameter introduces a trade-off between the precision and the recall of the algorithm, as higher values of the threshold lead to higher precision and lower recall, and lower values lead to higher recall and lower precision. In this paper, we propose a stacking approach for threshold-based classifiers. It runs several instances of classifiers corresponding to different thresholds and use their predictions as a feature vector for a supervised learner. We show that this approach is able to break the trade-off between the precision and recall of the algorithm, increasing both at the same time and enhancing the overall performance of the algorithm. We also show that this hybrid approach performs better and is less dependent on the amount of available training data with respect to a supervised learning approach that directly uses properties’ similarity values. In order to test the generality of the claim, we have run experimental tests using two different threshold-based classifiers on two different data sets. Finally, we show a concrete use case describing the implementation of the proposed approach in the generation of the 3cixty Nice knowledge base

Vocabularies for description of accessibility issues in multimodal user interfaces

In previous work, we proposed a unified approach for describing multimodal human-computer interaction and interaction constraints in terms of sensual, motor, perceptual and cognitive functions of users. In this paper, we extend this work by providing formalised vocabularies that express human functionalities and anatomical structures required by specific modalities. The central theme of our approach is to connect these modality representations with descriptions of user, device and environmental constraints that influence the interaction. These descriptions can then be used in a reasoning framework that will exploit formal connections among interaction modalities and constraints. The focus of this paper is on specifying a comprehensive vocabulary of necessary concepts. Within the context of an interaction framework, we describe a number of examples that use this formalised knowledge

Multimedia Annotation Interoperability Framework

Multimedia systems typically contain digital documents of mixed media types, which are indexed on the basis of strongly divergent metadata standards. This severely hamplers the inter-operation of such systems. Therefore, machine understanding of metadata comming from different applications is a basic requirement for the inter-operation of distributed Multimedia systems. In this document, we present how interoperability among metadata, vocabularies/ontologies and services is enhanced using Semantic Web technologies. In addition, it provides guidelines for semantic interoperability, illustrated by use cases. Finally, it presents an overview of the most commonly used metadata standards and tools, and provides the general research direction for semantic interoperability using Semantic Web technologies

Vocabularies for description of accessibility issues in multimodal user interfaces

In previous work, we proposed a unified approach for describing multimodal human-computer interaction and interaction constraints in terms of sensual, motor, perceptual and cognitive functions of users. In this paper, we extend this work by providing formalised vocabularies that express human functionalities and anatomical structures required by specific modalities. The central theme of our approach is to connect these modality representations with descriptions of user, device and environmental constraints that influence the interaction. These descriptions can then be used in a reasoning framework that will exploit formal connections among interaction modalities and constraints. The focus of this paper is on specifying a comprehensive vocabulary of necessary concepts. Within the context of an interaction framework, we describe a number of examples that use this formalised knowledge