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Abstract
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.
Original language | English |
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Publication status | Published - 1 Sept 2016 |
Keywords
- RAGE
- semantic annotation
- semantic content annotation
- automated text classification
- topic extraction
- ReaderBench
Fingerprint
Dive into the research topics of 'D6.3 – Semantic Content Annotation Support'. Together they form a unique fingerprint.Projects
- 1 Finished
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Rage: Realising an Applied Gaming Eco-system
Westera, W. (PI), Georgiadis, K. (CoI), Saveski, G. (CoI), van Lankveld, G. (CoI), Bahreini, K. (CoI), van der Vegt, W. (CoI), Berkhout, J. (CoI), Nyamsuren, E. (CoI), Kluijfhout, E. (CoI) & Nadolski, R. (CoI)
1/02/15 → 31/07/19
Project: Research