Entities, Topics and Events in Community Memories Full text

Elena Demidova, Nicola Barbieri, Stefan Dietze, Adam Funk, Gerhard Gossen, Diana Maynard, Nikos Papailiou, Vassilis Plachouras, Wim Peters, Thomas Risse, Yannis Stavrakas, Nina Tahmasebi
1st International Workshop on Archiving Community Memories (ARCOMEM), in conjunction with iPRES2013
Abstract. This 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.