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Analysing Entities, Topics and Events in Community Memories.

Elena Demidova ; N. Barbieri ; Stefan Dietze ; Adam Funk ; Gerhard Gossen ; Diana Maynard ; N. Papailiou ; V. Plachouras ; W. Peters ; Y. Stavrakas ; Thomas Risse ; Nina Tahmasebi (Institutionen för data- och informationsteknik (Chalmers))
Proc. of the first International Workshop on Archiving Community Memories (2013)
[Konferensbidrag, refereegranskat]

his paper briefly describes the components of the ARCOMEM architecture concerned with the extraction, enrichment, consolidation and dynamics analysis of entities, topics and events, deploying text mining, NLP, and semantic data integration technologies. In particular, we focus on four main areas relevant to support the ARCOMEM requirements and use cases: (a) entity and event extraction from text; (b) entity and event enrichment and consolidation; (c) topic detection and dynamics; and (d) temporal aspects and dynamics detection in Web language and online social networks.

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Denna post skapades 2014-01-07.
CPL Pubid: 191624