Congratulations to José Luis Redondo-García, Giuseppe Rizzo and Raphaël Troncy (all from LinkedTV partner EURECOM) who won the best paper award with their work on “The Concentric Nature of News Semantic Snapshots: Knowledge Extraction for Semantic Annotation of News Items“.

Single news articles on the Web often give a limited picture of the story being reported. There is sufficient information available on the Web to enrich the article and provide a broader picture of the reported story. The authors propose a concentric-based approach that enables to represent the context of a news item. Representative entities are collected via named-entity recognition and entity expansion. These entities are then harmonized into a single model and arranged according to different dimensions such as frequency (core), informativeness, semantic connectivity, and popularity (Crust).

The work from the paper draws from LinkedTV R&D in semantically enriching news broadcasts with related entities and news articles from the Web which was used in the scenario and demonstrator called LinkedNews. The technology for that scenario is part open source part commercial, see the list of LinkedTV tools & services as well as the LinkedNews showcase!

Paper description courtesy KCAP 2015 trip report by Martine de vos.

Tags: linkednews, named entity extractors, Named Entity Recognition, named entity recognition and disambiguation, NER, NERD, news, News show scenario

Posted in News Presentation
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