What fresh media are you looking for?: retrieving media items from multiple social networks
Proceedings of the 2012 international workshop on Socially-aware multimedia
Live topic generation from event streams
Proceedings of the 22nd international conference on World Wide Web companion
Enriching media fragments with named entities for video classification
Proceedings of the 22nd international conference on World Wide Web companion
MediaFinder: collect, enrich and visualize media memes shared by the crowd
Proceedings of the 22nd international conference on World Wide Web companion
Aggregating semantic annotators
Proceedings of the VLDB Endowment
ROSeAnn: reconciling opinions of semantic annotators
Proceedings of the VLDB Endowment
Identifying the Truth: Aggregation of Named Entity Extraction Results
Proceedings of International Conference on Information Integration and Web-based Applications & Services
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Named Entity Extraction is a mature task in the NLP field that has yielded numerous services gaining popularity in the Semantic Web community for extracting knowledge from web documents. These services are generally organized as pipelines, using dedicated APIs and different taxonomy for extracting, classifying and disambiguating named entities. Integrating one of these services in a particular application requires to implement an appropriate driver. Furthermore, the results of these services are not comparable due to different formats. This prevents the comparison of the performance of these services as well as their possible combination. We address this problem by proposing NERD, a framework which unifies 10 popular named entity extractors available on the web, and the NERD ontology which provides a rich set of axioms aligning the taxonomies of these tools.