Enriching Videos with Light Semantics
نویسندگان
چکیده
This paper describes an ongoing prototypical framework to annotate and retrieve web videos with light semantics. The proposed framework reuses many existing vocabularies along with a video model. The knowledge is captured from three different information spaces (media content, context, document). We also describe ways to extract the semantic content descriptions from the existing usergenerated content using multiple approaches of linguistic processing and Named Entity Recognition, which are later identified with DBpedia resources to establish meanings for the tags. Finally, the implemented prototype is described with multiple search interfaces and retrieval processes. Evaluation on semantic enrichment shows a considerable (50% of videos) improvement in content description.
منابع مشابه
Enriching user profiles using geo-social place semantics in geo-folksonomies
Enriching user profiles using geo-social place semantics in geo-folksonomies Ehab ElGindy & Alia Abdelmoty To cite this article: Ehab ElGindy & Alia Abdelmoty (2014) Enriching user profiles using geosocial place semantics in geo-folksonomies, International Journal of Geographical Information Science, 28:7, 1439-1458, DOI: 10.1080/13658816.2014.894194 To link to this article: http://dx.doi.org/1...
متن کاملModeling and Annotating the Expressive Semantics of Dance Videos
Dance videos are interesting and semantics-intensive. At the same time, they are the complex type of videos compared to all other types such as sports, news and movie videos. In fact, dance video is the one which is less explored by the researchers across the globe. Dance videos exhibit rich semantics such as macro features and micro features and can be classified into several types. Hence, the...
متن کاملBridging the Gap: Enriching YouTube Videos with Jazz Music Annotations
Web services allow permanent access to music from all over the world. Especially in the case of web services with user-supplied content, e.g., YouTubeTM, the available metadata is often incomplete or erroneous. On the other hand, a vast amount of high-quality and musically relevant metadata has been annotated in research areas such as Music Information Retrieval (MIR). Although they have great ...
متن کاملUNED at MediaEval 2010: exploiting text metadata for Automatic Video Tagging
In this paper we present the first participation of the NLP&IR group at UNED in the Tagging Task (Professional Version): prediction of semantic theme. This categorization task was carried out by an information retrieval approach, together with language models and clustering using only metadata associated with the videos. The results show that language models are useful for enriching the represe...
متن کامل