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SemanticNews: Enriching publishing of news stories

SemanticNews: Enriching publishing of news stories
SemanticNews: Enriching publishing of news stories
A central goal for the EPSRC funded Semantic Media Network project is to support interesting collaboration opportunities between researchers in order to foster relationships and encourage working together (EPSRC priority 'Working Together'). SemanticNews was one of the four projects funded in the first round of Semantic Media Network mini-projects, and was collaboration between the Universities of Southampton and Sheffield, together with the BBC.
The SemanticNews project aimed to promote people's comprehension and assimilation of news by augmenting broadcast news discussion and debate with information from the semantic web in the form of linked open data (LOD). The project has laid the foundations for a toolkit for (semi- ) automatic provision of semantic analysis and contextualization of the discussion of current events, encompassing state of the art semantic web technologies including text mining, consolidation against Linked Open Data, and advanced visualisation.
SemanticNews was bootstrapped using episodes of the BBC Question Time programme that already had transcripts and manually curated metadata, which included a list of the topical questions being debated. This information was used to create a workflow that a) extracts relevant entities using established named entity recognition techniques to identify the types of information to contextualise for a news article; b) provides associations with concepts from LOD resources; and, c) visualises the context using information derived from the LOD cloud.
This document forms the final report of the SemanticNews project, and describes in detail the processes and techniques explored for the enrichment of Question Time episodes. The final section of the report discusses how this work could be expanded in the future, and also makes a few recommendations for additional data that could be could be captured during the production process that would make the automatic generation of the contextualisation easier.
University of Southampton
Hare, Jonathon
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Newman, David
eb21ecdd-5ad0-49ec-9dd0-5bf98dc0c6f9
Peters, Wim
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Greenwood, Mark
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Eggink, Jana
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Hare, Jonathon, Newman, David, Peters, Wim, Greenwood, Mark and Eggink, Jana (2014) SemanticNews: Enriching publishing of news stories University of Southampton

Hare, Jonathon, Newman, David, Peters, Wim, Greenwood, Mark and Eggink, Jana (2014) SemanticNews: Enriching publishing of news stories University of Southampton

Record type: Monograph (Project Report)

Abstract

A central goal for the EPSRC funded Semantic Media Network project is to support interesting collaboration opportunities between researchers in order to foster relationships and encourage working together (EPSRC priority 'Working Together'). SemanticNews was one of the four projects funded in the first round of Semantic Media Network mini-projects, and was collaboration between the Universities of Southampton and Sheffield, together with the BBC.
The SemanticNews project aimed to promote people's comprehension and assimilation of news by augmenting broadcast news discussion and debate with information from the semantic web in the form of linked open data (LOD). The project has laid the foundations for a toolkit for (semi- ) automatic provision of semantic analysis and contextualization of the discussion of current events, encompassing state of the art semantic web technologies including text mining, consolidation against Linked Open Data, and advanced visualisation.
SemanticNews was bootstrapped using episodes of the BBC Question Time programme that already had transcripts and manually curated metadata, which included a list of the topical questions being debated. This information was used to create a workflow that a) extracts relevant entities using established named entity recognition techniques to identify the types of information to contextualise for a news article; b) provides associations with concepts from LOD resources; and, c) visualises the context using information derived from the LOD cloud.
This document forms the final report of the SemanticNews project, and describes in detail the processes and techniques explored for the enrichment of Question Time episodes. The final section of the report discusses how this work could be expanded in the future, and also makes a few recommendations for additional data that could be could be captured during the production process that would make the automatic generation of the contextualisation easier.

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More information

Published date: 9 January 2014
Organisations: Web & Internet Science

Identifiers

Local EPrints ID: 366832
URI: http://eprints.soton.ac.uk/id/eprint/366832
PURE UUID: 6ca0b562-d6f5-46fe-831a-1adac7e0828d
ORCID for Jonathon Hare: ORCID iD orcid.org/0000-0003-2921-4283
ORCID for David Newman: ORCID iD orcid.org/0000-0001-5153-5396

Catalogue record

Date deposited: 11 Jul 2014 13:53
Last modified: 18 Jul 2017 02:07

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Contributors

Author: Jonathon Hare ORCID iD
Author: David Newman ORCID iD
Author: Wim Peters
Author: Mark Greenwood
Author: Jana Eggink

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