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Martin Riedl 0002
Person information
- affiliation: University of Stuttgart, Institute for Natural Language Processing, Germany
- affiliation: University of Hamburg, Department of Informatics, Germany
- affiliation: TU Darmstadt, Computer Science Department, Germany
Other persons with the same name
- Martin Riedl 0001 — Bundeswehr University Munich, Institute for Applied Computer Science (and 1 more)
- Martin Riedl 0003 — Hochschule Mannheim, Germany
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2020 – today
- 2022
- [j6]Jaap Verheul, Hannu Salmi, Martin Riedl, Asko Nivala, Lorella Viola, Jana Keck, Emily Bell:
Using word vector models to trace conceptual change over time and space in historical newspapers, 1840-1914. Digit. Humanit. Q. 16(2) (2022) - [c27]Sophie Rentschler, Martin Riedl, Christian Stab, Martin Rückert:
Data Augmentation for Intent Classification of German Conversational Agents in the Finance Domain. KONVENS 2022: 1-7
2010 – 2019
- 2019
- [c26]Martin Riedl, Daniela Betz, Sebastian Padó
:
Clustering-Based Article Identification in Historical Newspapers. LaTeCH@NAACL-HLT 2019: 12-17 - [e4]Dmitry Ustalov, Swapna Somasundaran, Peter Jansen, Goran Glavas, Martin Riedl, Mihai Surdeanu, Michalis Vazirgiannis:
Proceedings of the Thirteenth Workshop on Graph-Based Methods for Natural Language Processing, TextGraphs@EMNLP 2019, Hong Kong, November 4, 2019. Association for Computational Linguistics 2019, ISBN 978-1-950737-86-4 [contents] - 2018
- [j5]Martin Riedl, Chris Biemann:
Using Semantics for Granularities of Tokenization. Comput. Linguistics 44(3) (2018) - [j4]Flavio Massimiliano Cecchini
A comparison of graph-based word sense induction clustering algorithms in a pseudoword evaluation framework. Lang. Resour. Evaluation 52(3): 733-770 (2018) - [c25]Martin Riedl, Sebastian Padó
A Named Entity Recognition Shootout for German. ACL (2) 2018: 120-125 - [c24]Ahmed Elsafty, Martin Riedl, Chris Biemann:
Document-based Recommender System for Job Postings using Dense Representations. NAACL-HLT (3) 2018: 216-224 - [e3]Goran Glavas, Swapna Somasundaran, Martin Riedl, Eduard H. Hovy:
Proceedings of the Twelfth Workshop on Graph-Based Methods for Natural Language Processing, TextGraphs@NAACL-HLT 2018, New Orleans, Louisiana, USA, June 6, 2018. Association for Computational Linguistics 2018, ISBN 978-1-948087-25-4 [contents] - 2017
- [c23]Seid Muhie Yimam, Sanja Stajner, Martin Riedl, Chris Biemann:
CWIG3G2 - Complex Word Identification Task across Three Text Genres and Two User Groups. IJCNLP(2) 2017: 401-407 - [c22]Martin Riedl, Chris Biemann:
There's no 'Count or Predict' but task-based \\selection for distributional models. IWCS(2) 2017 - [c21]Prasanth Kolachina, Martin Riedl, Chris Biemann:
Replacing OOV Words For Dependency Parsing With Distributional Semantics. NODALIDA 2017: 11-19 - [c20]Flavio Massimiliano Cecchini, Chris Biemann, Martin Riedl:
Using Pseudowords for Algorithm Comparison: An Evaluation Framework for Graph-based Word Sense Induction. NODALIDA 2017: 105-114 - [c19]Seid Muhie Yimam
Multilingual and Cross-Lingual Complex Word Identification. RANLP 2017: 813-822 - [e2]Martin Riedl, Swapna Somasundaran, Goran Glavas, Eduard H. Hovy:
Proceedings of TextGraphs@ACL 2017: the 11th Workshop on Graph-based Methods for Natural Language Processing, Vancouver, Canada, August 3, 2017. Association for Computational Linguistics 2017, ISBN 978-1-945626-60-9 [contents] - 2016
- [b1]Martin Riedl:
Unsupervised Methods for Learning and Using Semantics of Natural Language. Darmstadt University of Technology, Germany, 2016, pp. 1-240 - [c18]Martin Riedl, Tim Feuerbach, Chris Biemann:
Running into Brick Walls Attempting to Improve a Simple Unsupervised Parser. KONVENS 2016 - [c17]Alexander Panchenko, Johannes Simon, Martin Riedl, Chris Biemann:
Noun Sense Induction and Disambiguation using Graph-Based Distributional Semantics. KONVENS 2016 - [c16]Martin Riedl, Chris Biemann:
Impact of MWE Resources on Multiword Recognition. MWE@ACL 2016 - [c15]Seid Muhie Yimam
Learning Paraphrasing for Multiword Expressions. MWE@ACL 2016 - [c14]Martin Riedl, Chris Biemann:
Unsupervised Compound Splitting With Distributional Semantics Rivals Supervised Methods. HLT-NAACL 2016: 617-622 - [e1]Tanmoy Chakraborty, Martin Riedl, V. G. Vinod Vydiswaran:
Proceedings of TextGraphs@NAACL-HLT 2016: the 10th Workshop on Graph-based Methods for Natural Language Processing, June 17, 2016, San Diego, California, USA. The Association for Computer Linguistics 2016, ISBN 978-1-941643-88-4 [contents] - 2015
- [j3]Sunny Mitra, Ritwik Mitra, Suman Kalyan Maity, Martin Riedl, Chris Biemann, Pawan Goyal, Animesh Mukherjee:
An automatic approach to identify word sense changes in text media across timescales. Nat. Lang. Eng. 21(5): 773-798 (2015) - [c13]Eugen Ruppert, Manuel Kaufmann, Martin Riedl, Chris Biemann:
JoBimViz: A Web-based Visualization for Graph-based Distributional Semantic Models. ACL (System Demonstrations) 2015: 103-108 - [c12]Martin Riedl, Chris Biemann:
A Single Word is not Enough: Ranking Multiword Expressions Using Distributional Semantics. EMNLP 2015: 2430-2440 - [c11]Eugen Ruppert, Jonas Klesy, Martin Riedl, Chris Biemann:
Rule-based Dependency Parse Collapsing and Propagation for German and English. GSCL 2015: 58-66 - [c10]Tim Feuerbach, Martin Riedl, Chris Biemann:
Distributional Semantics for Resolving Bridging Mentions. RANLP 2015: 192-199 - 2014
- [c9]Sunny Mitra, Ritwik Mitra, Martin Riedl, Chris Biemann, Animesh Mukherjee, Pawan Goyal:
That's sick dude!: Automatic identification of word sense change across different timescales. ACL (1) 2014: 1020-1029 - [c8]Martin Riedl, Irina Alles, Chris Biemann:
Combining Supervised and Unsupervised Parsing for Distributional Similarity. COLING 2014: 1435-1446 - [c7]Martin Riedl, Michael R. Glass, Alfio Massimiliano Gliozzo
Lexical Substitution for the Medical Domain. EMNLP 2014: 610-614 - [c6]Martin Riedl, Richard Steuer, Chris Biemann:
Distributed Distributional Similarities of Google Books over the Centuries. LREC 2014: 1401-1405 - [i1]Sunny Mitra, Ritwik Mitra, Martin Riedl, Chris Biemann, Animesh Mukherjee, Pawan Goyal:
That's sick dude!: Automatic identification of word sense change across different timescales. CoRR abs/1405.4392 (2014) - 2013
- [j2]Chris Biemann, Martin Riedl:
Text: now in 2D! A framework for lexical expansion with contextual similarity. J. Lang. Model. 1(1): 55-95 (2013) - [c5]Janneke Rauscher, Leonard Swiezinski, Martin Riedl, Chris Biemann:
Exploring Cities in Crime: Significant Concordance and Co-occurrence in Quantitative Literary Analysis. CLfL@NAACL-HLT 2013: 61-71 - [c4]Martin Riedl, Chris Biemann:
Scaling to Large3 Data: An Efficient and Effective Method to Compute Distributional Thesauri. EMNLP 2013: 884-890 - [c3]Chris Biemann, Bonaventura Coppola, Michael R. Glass, Alfio Gliozzo, Matthew Hatem, Martin Riedl:
JoBimText Visualizer: A Graph-based Approach to Contextualizing Distributional Similarity. TextGraphs@EMNLP 2013: 6-10 - [c2]Martin Riedl, Chris Biemann:
From Global to Local Similarities: A Graph-Based Contextualization Method using Distributional Thesauri. TextGraphs@EMNLP 2013: 39-43 - 2012
- [j1]Martin Riedl, Chris Biemann:
Text Segmentation wit h Topic Models. J. Lang. Technol. Comput. Linguistics 27(1): 47-69 (2012) - [c1]Martin Riedl, Chris Biemann:
How Text Segmentation Algorithms Gain from Topic Models. HLT-NAACL 2012: 553-557
Coauthor Index
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last updated on 2024-05-31 02:29 CEST by the dblp team
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