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conTEXT - a mashup platform for lightweight text analytics

 
: Khalili, A.

:
Volltext (PDF; )

Stefanidakis, M.:
AI Mashup Challenge 2014. Proceedings : Co-located with 11th Extended Semantic Web Conference, ESWC 2014, Crete, Greece, May 27, 2014
Crete, 2014 (CEUR Workshop Proceedings 1200)
Paper 5, 10 S.
AI Mashup Challenge <2014, Crete>
Extended Semantic Web Conference (ESWC) <11, 2014, Crete>
Englisch
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IAIS ()

Abstract
Social media technologies such as Weblogs, Microblogging, Wikis and Social Networks have become one of the most important parts of our daily life as they enable us to communicate and share stories with a lot of people. The more the amount of published information grows, the more important are solutions for accessing, analyzing, summarizing and visualizing information. While substantial progress has been made in the last years in each of these areas individually, we argue, that only the intelligent combination of approaches will make this progress truly useful and leverage further synergies between techniques. conTEXT aims to provide a user-friendly and lightweight Mashup platform enabling end-users to use sophisticated NLP techniques for analyzing and visualizing their content. it provides a flexible text analytics architecture of participation by innovative combination of different pieces of services for content collection and analysis. Named Entity Recognition (e.g. D Bpedia Spotlight, FOX), Relation Extraction (e.g. BOA), Sentiment Analysis (e.g. Vivekn), Social Media (e.g. Twitter, Fcebook, Google+, LinkedIn), and Visualization (e.g. Exhibit, D3js) are some of the example services and APIs currently utilized in conTEXT.

: http://publica.fraunhofer.de/dokumente/N-351145.html