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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 3 4 Hits 1 – 20 of 79 1 Wissensrohstoff Text : Eine Einführung in das Text Mining Biemann, Chris (VerfasserIn); Heyer, Gerhard (VerfasserIn). - 2., wesentl. überarb. Auflage 2022. - Wiesbaden : Springer Fachmedien Wiesbaden GmbH, 2022 IDS Mannheim Show details 2 Language Models Explain Word Reading Times Better Than Empirical Predictability ... Hofmann, Markus J.; Remus, Steffen; Biemann, Chris. - : arXiv, 2022 BASE Show details 3 SCoT: Sense Clustering over Time: a tool for the analysis of lexical change ... Haase, Christian; Anwar, Saba; Yimam, Seid Muhie; Friedrich, Alexander; Biemann, Chris. - : arXiv, 2022 Abstract: We present Sense Clustering over Time (SCoT), a novel network-based tool for analysing lexical change. SCoT represents the meanings of a word as clusters of similar words. It visualises their formation, change, and demise. There are two main approaches to the exploration of dynamic networks: the discrete one compares a series of clustered graphs from separate points in time. The continuous one analyses the changes of one dynamic network over a time-span. SCoT offers a new hybrid solution. First, it aggregates time-stamped documents into intervals and calculates one sense graph per discrete interval. Then, it merges the static graphs to a new type of dynamic semantic neighbourhood graph over time. The resulting sense clusters offer uniquely detailed insights into lexical change over continuous intervals with model transparency and provenance. SCoT has been successfully used in a European study on the changing meaning of `crisis'. ... : Update of https://aclanthology.org/2021.eacl-demos.23/ ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://dx.doi.org/10.48550/arxiv.2203.09892 https://arxiv.org/abs/2203.09892 BASE Hide details 4 Language Models Explain Word Reading Times Better Than Empirical Predictability Hofmann, Markus J.; Remus, Steffen; Biemann, Chris... In: Front Artif Intell (2022) BASE Show details 5 Probing Pre-trained Language Models for Semantic Attributes and their Values ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Beloucif, Meriem; Biemann, Chris. - : Underline Science Inc., 2021 BASE Show details 6 WebAnno-MM: EXMARaLDA meets WebAnno Remus, Steffen [Verfasser]; Hedeland, Hanna [Verfasser]; Ferger, Anne [Verfasser]. - Mannheim : Leibniz-Institut für Deutsche Sprache (IDS), Bibliothek, 2020 DNB Subject Category Language Show details 7 Comparison of Different Lexical Resources With Respect to the Tip-of-the-Tongue Problem Zock, Michael; Biemann, Chris In: ISSN: 1598-2327 ; EISSN: 1976-6939 ; Journal of Cognitive Science ; https://hal.archives-ouvertes.fr/hal-03168850 ; Journal of Cognitive Science, Institute for Cognitive Science, Seoul National University, 2020, 21 (2), pp.193-252. &#x27E8;10.17791/jcs.2020.21.2.193&#x27E9; (2020) BASE Show details 8 Introducing various Semantic Models for Amharic: Experimentation and Evaluation with multiple Tasks and Datasets ... Yimam, Seid Muhie; Ayele, Abinew Ali; Venkatesh, Gopalakrishnan. - : arXiv, 2020 BASE Show details 9 Word Sense Disambiguation for 158 Languages using Word Embeddings Only ... Logacheva, Varvara; Teslenko, Denis; Shelmanov, Artem. - : arXiv, 2020 BASE Show details 10 Individual corpora predict fast memory retrieval during reading ... The 28th International Conference on Computational Linguistics 2020; Biemann, Chris; Hofmann, Markus J.. - : Underline Science Inc., 2020 BASE Show details 11 Individual corpora predict fast memory retrieval during reading ... Hofmann, Markus J.; Müller, Lara; Rölke, Andre. - : arXiv, 2020 BASE Show details 12 Token-based spelling variant detection in Middle Low German texts [<Journal>] Barteld, Fabian [Verfasser]; Biemann, Chris [Verfasser]; Zinsmeister, Heike [Verfasser] DNB Subject Category Language Show details 13 Unsupervised Induction of Domain Dependency Graphs - Extracting, Understanding and Visualizing Domain Knowledge Kohail, Sarah [Verfasser]; Biemann, Chris [Akademischer Betreuer]. - Hamburg : Staats- und Universitätsbibliothek Hamburg, 2019 DNB Subject Category Language Show details 14 Making Fast Graph-based Algorithms with Graph Metric Embeddings ... Kutuzov, Andrey; Dorgham, Mohammad; Oliynyk, Oleksiy. - : arXiv, 2019 BASE Show details 15 On the Compositionality Prediction of Noun Phrases using Poincaré Embeddings ... Jana, Abhik; Puzyrev, Dmitry; Panchenko, Alexander. - : arXiv, 2019 BASE Show details 16 Every child should have parents: a taxonomy refinement algorithm based on hyperbolic term embeddings ... Aly, Rami; Acharya, Shantanu; Ossa, Alexander. - : arXiv, 2019 BASE Show details 17 Datasets for Watset: Local-Global Graph Clustering with Applications in Sense and Frame Induction ... Ustalov, Dmitry; Panchenko, Alexander; Biemann, Chris. - : Zenodo, 2019 BASE Show details 18 Datasets for Watset: Local-Global Graph Clustering with Applications in Sense and Frame Induction ... Ustalov, Dmitry; Panchenko, Alexander; Biemann, Chris. - : Zenodo, 2019 BASE Show details 19 Adaptive Approaches to Natural Language Processing in Annotation and Application ; Adaptive Ansätze zur Verarbeitung natürlicher Sprache in Annotation und Anwendung Yimam, Seid Muhie. - : Staats- und Universitätsbibliothek Hamburg Carl von Ossietzky, 2019 BASE Show details 20 HHMM at SemEval-2019 Task 2: Unsupervised frame induction using contextualized word embeddings Arefyev, Nikolay; Panchenko, Alexander; Anwar, Saba. - : Association for Computational Linguistics, ACL, 2019 BASE Show details Page: 1 2 3 4

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