Wortschatz
Dr. Michael Richter
Phone: +49 341-97-32315 Address: |
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aktuelle Projekte
- DFG-Projekt: Information distribution and language structure - correlation of grammatical expressions of the noun/verb distinction and lexical information content in Tagalog, Indonesian and German
- DFG-Project: Actionality classes and cross-linguistic coding tendencies. Typological research and development of an analysis software tool
Publications
2023-
[scherihou]
Scheffler, Tatjana, Richter, Michael, van Hout, Roeland: Tracing and classifying German intensifiers via information theory . In: Language Sciences 96 (https://doi.org/10.1016/j.langsci.2022.101535), Elsevier, 2023
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[RiBaKöKyPhYoHeHi]
Michael Richter, Maria Bardají i Farré, Max Kölbl, Yuki Kyogoku, Jonas Nathanael Philipp, Tariq Yousef, Gerhard Heyer, and Nikolaus P. Himmelmann: Uniform Density in Linguistic Information derived from Dependency Structures. In: Proceedings of the 14th International Conference on Agents and Artificial Intelligence (Vol. 1), NLPinAI at ICAART, 2022
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[KöKyPhiRiRieYou1]
Max Kölbl, Yuki Kyogoku, J. Nathanael Philipp, Michael Richter, Clemens Rietdorf, Tariq Youssef: Beyond the Failure of Direct-Matching in Keyword Evaluation: A Sketch of a Graph Based Solution. In: Front. Artif. Intell. 5:801564. doi: 10.3389/frai.2022.801564, 2022
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[PhKöKyYoRi]
J.N. Philipp, Max Kölbl, Yuki Kyogoku, Tariq Yousef, and Michael Richter: One Step Beyond: Keyword Extraction in German Utilising Surprisal from Topic Contexts. In: Intelligent Computing. SAI 2022. Lecture Notes in Networks and Systems, Springer, Cham, 2022
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[KöKyPhiRiRieYou]
Max Kölbl, Yuki Kyogoku, J. Nathanael Philipp, Michael Richter, Clemens Rietdorf, Tariq Yousef: The Semantic Level of Shannon Information: Are Highly Informative Words Good Keywords? A Study on German. In: Natural Language Processing in Artificial Intelligence—NLPinAI 2020, Springer, 2021
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[RvH20]
Michael Richter and Roeland van Hout: Ranking Dutch intensifiers: a usage-based approach. In: Language and Cognition, Cambridge University Press, 2020
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[KöKyPhiRiRieYo]
Max Kölbl, Yuki Kyogoku, Nathanael Philipp, Michael Richter, Clemens Rietdorf, and Tariq Yousef: Keyword extraction in German: Information-theory vs. deep learning . In: Proceedings of the 12th International Conference on Agents and Artificial Intelligence, Vol. 1, 459 - 464, 2020
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[RiYou4]
Michael Richter and Tariq Yousef: Information from topic contexts: the prediction of aspectual coding of verbs in Russian. SIGTYP workshop at EMNLP 2020 (https://sigtyp.github.io/workshops/2020/papers/2.pdf), 2020
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[RHN]
Michael Richter, Jürgen Hermes, and Claes Neuefeind: Aspectual classifications: Use of raters’ associations and co-occurrences of verbs for aspectual classification in German. In: Agents and Artificial Intelligence, Springer, 2019
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[RiKyKö]
Michael Richter, Yuki Kyogoku and Max Kölbl: Interaction of Information Content and Frequency as predictors of verbs' lengths. In: Business Information Systems, Springer, 2019
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[RiKyoKö]
Michael Richter, Yuki Kyogoku and Max Kölbl: Estimation of Average Information Content: Comparison of Impact of Contexts. In: Intelligent Systems and Applications. IntelliSys 2019, Springer, Cham, 2019
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[RiYou]
Michael Richter and Tariq Yousef: Predicting default and non-default aspectual coding: Impact and density of information features. Proceedings of the 15th Conference on Natural Language Processing (KONVENS 2019): Kaleidoscope Abstracts - German Society for Computational Linguistics & Language Technology, 2019
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[RiYou2]
: Predicting default and non-default aspectual coding: Impact and density of information features. Proceedings of the 3rd Workshop on Natural Language for Artificial Intelligence co-located with the 18th International Conference of the Italian Association for Artificial Intelligence (AIIA 2019), 2019
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[RiCe]
Michael Richter and Giuseppe G.A. Celano: Aspectual Coding Asymmetries: Predicting Aspectual Verb Lengths by the Effects Frequency and Information Content. In: Topics in Linguistics, de Gruyter, 2019
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[HRN18]
Jürgen Hermes, Michael Richter, and Claes Neuefeind: Supervised Classification of Aspectual Verb Classes in German. Subcategorization-Frame-Based vs Window-Based Approach: A Comparison. In: Proceedings of ICAART 2018. 10th International Conference on Agents and Artificial Intelligence, 2018
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[CRVH]
Giuseppe Celano, Michael Richter, Rebecca Voll, and Gerhard Heyer: Aspect Coding Asymmetries of Verbs: The Case of Russian. In: KONVENS 2018. PROCEEDINGS of the 14th Conference on Natural Language Processing, 2018
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[RvH18_2]
Michael Richter and Roeland van Hout: Aspectual coercion of telic verbs and atelic adverbials in German: Acceptability judgments on sentences with conflicting aspectual information by native speakers. In: Lingua, 2018
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[RvH17]
Michael Richter and Roeland van Hout: How WIE 'how' as Intensifer Co-occurs with other Intensifers in German Sentences. In: Proceedings of the Workshop on Logic and Algorithms in Computational Linguistics 2017 (LACompLing2017), 2017
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[RvH16]
Michael Richter and Roeland van Hout: Transitivity in similarities judgments on German verbs: disclosing lexical categories and aspectual types. In: The Mental Lexicon (11:1), 76-93, 2016
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[RvH16a]
Michael Richter and Roeland van Hout: A classification of German verbs using empirical data and conceptions of Vendler and Dowty. In: Sprache und Datenverarbeitung – International Journal for Language Data Processing 38. 1-2/2014: The language of mathematics computational, linguistic and logical aspects, 81 – 117., 2016
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[HRN15]
Jürgen Hermes, Michael Richter, and Claes Neuefeind: Automatic induction of German aspectual verb classes in a distributional framework. In: International Conference of the German Society for Computational Linguistics and Language Technology. Proceedings of the conference (GSCL 2015), 2015
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[R15]
Michael Richter: Schließen auf Verbklassen. In: Zeitschrift für germanistische Linguistik 43(2), 183 – 198, 2015
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[RiHe]
: Classification of German verbs using nouns in argument positions and aspectual features. 2015
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[RvH13]
Michael Richter and Roeland van Hout: Interpreting resultative sentences in German: stages in L1 acquisition. In: Linguistics 51(1), 117 – 144, 2013
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[RvH10]
Michael Richter and Roeland van Hout: Why some verbs can form a resultative construction while others cannot: decomposing Semantic Binding. In: Lingua 120 (8), 2006-2021, 2010
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Talks
11.10.13 The use of semantic associations for the classification of verbs,
Investigating Semantics: Empirical and Philosophical Approaches,
Ruhr Universität Bochum,
31.3.15 Classification of German verbs using nouns in argument positions and
aspectual features. NetWordS Final Conference, Scuola Normale Superiore, Pisa.
30.9.15 Automatic induction of German aspectual verb classes in a distributional
framework. GSCL 2015, Universität Duisburg-Essen.
16.1.18 Supervised Classification of Aspectual Verb Classes in German. Subcategorization-Frame-Based vs Window-Based Approach: A Comparison.
ICAART 2018. 10th International Conference on Agents and Artificial Intelligence, Funchal, Madeira.