D6.3 – Semantic Content Annotation Support


Autoria(s): Dascalu, Mihai; Gutu, Gabriel; Trausan-Matu, Stefan; Heutelbeck, Dominic
Data(s)

02/10/2016

02/10/2016

01/09/2016

Resumo

The Semantic Annotation component is a software application that provides support for automated text classification, a process grounded in a cohesion-centered representation of discourse that facilitates topic extraction. The component enables the semantic meta-annotation of text resources, including automated classification, thus facilitating information retrieval within the RAGE ecosystem. It is available in the ReaderBench framework (http://readerbench.com/) which integrates advanced Natural Language Processing (NLP) techniques. The component makes use of Cohesion Network Analysis (CNA) in order to ensure an in-depth representation of discourse, useful for mining keywords and performing automated text categorization. Our component automatically classifies documents into the categories provided by the ACM Computing Classification System (http://dl.acm.org/ccs_flat.cfm), but also into the categories from a high level serious games categorization provisionally developed by RAGE. English and French languages are already covered by the provided web service, whereas the entire framework can be extended in order to support additional languages.

This study is part of the RAGE project. The RAGE project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 644187. This publication reflects only the author's view. The European Commission is not responsible for any use that may be made of the information it contains.

Identificador

http://hdl.handle.net/1820/7068

Relação

info:eu-repo/grantAgreement/EC/H2020/644187/EU/Realising an Applied Gaming Eco-system/RAGE

Direitos

openAccess

Palavras-Chave #RAGE #semantic annotation #semantic content annotation #automated text classification #topic extraction #ReaderBench
Tipo

report