D6.3 – Semantic Content Annotation Support

Mihai Dascalu, Gabriel Gutu, Stefan Trausan-Matu, Dominic Heutelbeck

    Research output: Book/ReportDeliverableAcademic

    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 languageEnglish
    Publication statusPublished - 1 Sep 2016

    Keywords

    • RAGE
    • semantic annotation
    • semantic content annotation
    • automated text classification
    • topic extraction
    • ReaderBench

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  • Projects

    Rage: Realising an Applied Gaming Eco-system

    Westera, W., Georgiadis, K., Saveski, G., van Lankveld, G., Bahreini, K., van der Vegt, W., Berkhout, J., Nyamsuren, E., Kluijfhout, E. & Nadolski, R.

    1/02/1531/07/19

    Project: Research

    Cite this

    Dascalu, M., Gutu, G., Trausan-Matu, S., & Heutelbeck, D. (2016). D6.3 – Semantic Content Annotation Support.