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Maximilian Köper
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2010 – 2019
- 2018
- [c18]Eleri Aedmaa, Maximilian Köper, Sabine Schulte im Walde:
Combining Abstractness and Language-specific Theoretical Indicators for Detecting Non-Literal Usage of Estonian Particle Verbs. NAACL-HLT (Student Research Workshop) 2018: 9-16 - [c17]Maximilian Köper, Sabine Schulte im Walde:
Analogies in Complex Verb Meaning Shifts: the Effect of Affect in Semantic Similarity Models. NAACL-HLT (2) 2018: 150-156 - [c16]Sabine Schulte im Walde, Maximilian Köper, Sylvia Springorum:
Assessing Meaning Components in German Complex Verbs: A Collection of Source-Target Domains and Directionality. *SEM@NAACL-HLT 2018: 22-32 - 2017
- [c15]Maximilian Köper, Sabine Schulte im Walde:
Applying Multi-Sense Embeddings for German Verbs to Determine Semantic Relatedness and to Detect Non-Literal Language. EACL (2) 2017: 535-542 - [c14]Kim Anh Nguyen, Maximilian Köper, Sabine Schulte im Walde, Ngoc Thang Vu:
Hierarchical Embeddings for Hypernymy Detection and Directionality. EMNLP 2017: 233-243 - [c13]Maximilian Köper, Kim Anh Nguyen, Sabine Schulte im Walde:
Optimizing Visual Representations in Semantic Multi-modal Models with Dimensionality Reduction, Denoising and Contextual Information. GSCL 2017: 292-300 - [c12]Moritz Wittmann, Maximilian Köper, Sabine Schulte im Walde:
Exploring Soft-Clustering for German (Particle) Verbs across Frequency Ranges. IWCS(2) 2017 - [c11]Maximilian Köper, Sabine Schulte im Walde:
Complex Verbs are Different: Exploring the Visual Modality in Multi-Modal Models to Predict Compositionality. MWE@EACL 2017: 200-206 - [c10]Maximilian Köper, Evgeny Kim, Roman Klinger:
IMS at EmoInt-2017: Emotion Intensity Prediction with Affective Norms, Automatically Extended Resources and Deep Learning. WASSA@EMNLP 2017: 50-57 - [i1]Kim Anh Nguyen, Maximilian Köper, Sabine Schulte im Walde, Ngoc Thang Vu:
Hierarchical Embeddings for Hypernymy Detection and Directionality. CoRR abs/1707.07273 (2017) - 2016
- [c9]Maximilian Köper, Sabine Schulte im Walde:
Automatic Semantic Classification of German Preposition Types: Comparing Hard and Soft Clustering Approaches across Features. ACL (2) 2016 - [c8]Maximilian Köper, Sabine Schulte im Walde:
Automatically Generated Affective Norms of Abstractness, Arousal, Imageability and Valence for 350 000 German Lemmas. LREC 2016 - [c7]Maximilian Köper, Melanie Zaiß, Qi Han, Steffen Koch, Sabine Schulte im Walde:
Visualisation and Exploration of High-Dimensional Distributional Features in Lexical Semantic Classification. LREC 2016 - [c6]Maximilian Köper, Sabine Schulte im Walde:
Distinguishing Literal and Non-Literal Usage of German Particle Verbs. HLT-NAACL 2016: 353-362 - [c5]Maximilian Köper, Sabine Schulte im Walde, Max Kisselew, Sebastian Padó
:
Improving Zero-Shot-Learning for German Particle Verbs by using Training-Space Restrictions and Local Scaling. *SEM@ACL 2016 - 2015
- [c4]Maximilian Köper, Christian Scheible, Sabine Schulte im Walde:
Multilingual Reliability and "Semantic" Structure of Continuous Word Spaces. IWCS 2015: 40-45 - 2014
- [c3]Jason Utt, Sylvia Springorum, Maximilian Köper, Sabine Schulte im Walde:
Fuzzy V-Measure - An Evaluation Method for Cluster Analyses of Ambiguous Data. LREC 2014: 581-587 - [c2]Maximilian Köper, Sabine Schulte im Walde:
A Rank-based Distance Measure to Detect Polysemy and to Determine Salient Vector-Space Features for German Prepositions. LREC 2014: 4459-4466 - 2013
- [c1]Sabine Schulte im Walde, Maximilian Köper:
Pattern-Based Distinction of Paradigmatic Relations for German Nouns, Verbs, Adjectives. GSCL 2013: 184-198
Coauthor Index
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