UKP - Prof. Dr. Iryna Gurevych

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e-NLP

UKP Lab > Home > e-NLP
Educational Natural Language Processing (e-NLP) aims at
  • finding new applications of Natural Language Processing for educational purposes
  • developing new techniques and software taking into account the specific needs in the educational domain
We especially focus on NLP applications for eLearning 2.0, which is characterised by a worldwide learning community where educational material is produced both by students and teachers. This brings about new challenges for NLP since the amount of user-generated discourse and social media content such as wikis or blogs is constantly growing and requires intelligent automatic processing.

Objectives of Natural Language Processing for eLearning 2.0

  • Support eLearning 2.0 by mining and representing knowledge IN and FOR Web 2.0
  • Provide semantically-enhanced information management (information retrieval, question-answering, summarisation)
  • Analyse user-generated content (opinion mining, quality assesment)

Projects in Educational Natural Language Processing

  • SIR - Electronic career guidance. This project systematically investigates the possible usage of semantic and lexical relationships between words or concepts for improving the information retrieval process in the domain of electronic career guidance. The main focus is on semantic relatedness measures using different knowledge sources (e.g. WordNet, GermaNet, or Wikipedia).
  • QA-EL - Question Answering for discourse-based knowledge acquisition. The project investigates novel applications of dynamic lexical-semantic resources for information search in eLearning. On the one hand, we develop novel ways of mining knowledge from Wikipedia and other Web 2.0 knowledge repositories. On the other hand, we apply question answering in the area of discourse-based knolwedge acquisition in eLearning for the first time.
  • SENTAL - Sentiment Analysis for User-generated Discourse
  • EduWeb - Educational Web 2.0. This project explores the use of Natural Language Processing (NLP) and collaboratively constructed resources on the web (i.e. Wikipedia and Wiktionary) for innovative applications in technology enhanced education.
We also take part in the following joint software development projects at the UKP Lab:
  • WikiMining. This projects aims at providing structured access to information nuggets stored in Wikipedia and Wiktionary like redirects, categories, articles and link structure. Knowledge extracted from Wiktionary and Wikipedia is used in the SIR and QA-EL projects to enhance information retrieval and question answering for eLearning with semantic information.
  • Darmstadt Knowledge Processing (DKPro) Repository. All software developed within our research projects is integrated in the DKPro Repository.

Partners

Selected publications

PDF Abstract BibTeX Entry
Christof Müller, Iryna Gurevych, Max Mühlhäuser:
Integrating Semantic Knowledge into Text Similarity and Information Retrieval. In: Proceedings of the First IEEE International Conference on Semantic Computing (ICSC), pp. 257 - 264, 2007.
PDF Abstract BibTeX Entry
Jürgen Steimle, Iryna Gurevych, Max Mühlhäuser:
Notetaking in University Courses and its Implications on eLearning Systems. In: Tagungsband der fünften e-Learning Fachtagung Informatik. Christian Eibl, Johannes Magenheim, Sigrid Schubert, Martin (Eds.). pp. 45-56, Gesellschaft für Informatik e.V., Bonn, Germany, 2007. ISBN 978-3-88579-205-5.
PDF Abstract BibTeX Entry
Markus Weimer, Iryna Gurevych, Max Mühlhäuser:
Automatically Assessing the Post Quality in Online Discussions on Software. In: Companion Volume of the 45rd Annual Meeting of the Association for Computational Linguistics (ACL) . pp. 125-128, Association for Computational Linguistics, 2007.

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