Linked Open Data and the RDF format have become the premier method of publishing structured data representing entities and facts. Specifically, media organizations, such as the New York Times and the BBC, have embraced Linked Open Data as a way of providing structured access to traditional media content, including articles, images, and video. To ground RDF entities and predicates in existing Linked Open Data sources, dataset curators provide links for some entities to existing general purpose repositories, such as YAGO and DBpedia, using entity extraction and linking tools. However, these state-of-the-art tools rely on the entities to exist in the knowledge base. How much of the information is actually new and thus unable to be grounded is unclear. In this work, we empirically investigate the prevalence of new entities in news feeds with respect to both public and commercial knowledge graphs.
|Title of host publication||The Web Conference 2019 - Companion of the World Wide Web Conference, WWW 2019|
|Publisher||Association for Computing Machinery, Inc|
|Number of pages||8|
|State||Published - 13 May 2019|
|Event||2019 World Wide Web Conference, WWW 2019 - San Francisco, United States|
Duration: 13 May 2019 → 17 May 2019
|Name||The Web Conference 2019 - Companion of the World Wide Web Conference, WWW 2019|
|Conference||2019 World Wide Web Conference, WWW 2019|
|Period||13/05/19 → 17/05/19|
Bibliographical notePublisher Copyright:
© 2019 IW3C2 (International World Wide Web Conference Committee), published under Creative Commons CC-BY 4.0 License.
- Emerging entities
- Knowledge graph extension
ASJC Scopus subject areas
- Computer Networks and Communications