Distributional Models of Category Concepts Based on Names of Category Members-Reference-Cited by-同舟云学术

Distributional Models of Category Concepts Based on Names of Category Members

Published:2021-09 Issue:9 Volume:45 Page:
ISSN:0364-0213
Container-title:Cognitive Science
language:en
Short-container-title:Cognitive Science

Author:

Westera Matthijs¹^ORCID,Gupta Abhijeet²,Boleda Gemma³⁴,Padó Sebastian⁵

Affiliation:

1. Leiden University Centre for Linguistics Universiteit Leiden

2. Institut für Sprache und Information Heinrich‐Heine‐Universität Düsseldorf

3. Department of Translation and Language Sciences Universitat Pompeu Fabra

4. ICREA

5. Institut für Maschinelle Sprachverarbeitung University of Stuttgart

Funder

Deutsche Forschungsgemeinschaft

H2020 European Research Council

Universiteit Leiden

Publisher

Wiley

Subject

Artificial Intelligence,Cognitive Neuroscience,Experimental and Cognitive Psychology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/cogs.13029

Reference101 articles.

1. Abhishek A. A.&Awekar A.(2017). Fine‐grained entity type classification by jointly learning representations and label embeddings. In Proceedings of the conference of the European chapter of the Association for Computational Linguistics (pp. 797–807). Valencia Spain: Association for Computational Linguistics. Available at:https://aclanthology.org/E17‐1075/

2. Adel H.&Schütze H.(2014). Using mined coreference chains as a resource for a semantic task. In Proceedings of the 2014 conference on empirical methods in natural language processing (EMNLP) (pp. 1447–1452). Doha Qatar: Association for Computational Linguistics. Available at:https://www.aclweb.org/anthology/D14‐1151

3. Agirre E. Alfonseca E. Hall K. Kravalova J. Paşca M.&Soroa A.(2009). A study on similarity and relatedness using distributional and WordNet‐based approaches. In Proceedings of human language technologies: The 2009 annual conference of the North American chapter of the Association for Computational Linguistics Boulder CO (pp. 19–27). Available at:https://www.aclweb.org/anthology/N09‐1003

4. Aina L. Silberer C. Sorodoc I.‐T. Westera M. &Boleda G.(2019).What do entity‐centric models learn? Insights from entity linking in multi‐party dialogue. InProceedings of the 2019 conference of the North American chapter of the Association for Computational Linguistics: Human Language Technologies (long and short papers)(Vol.1 pp.3772–3783).Minneapolis MN:Association for Computational Linguistics. Available at:https://www.aclweb.org/anthology/N19‐1378

5. Alfonseca E.&Manandhar S.(2002). Distinguishing concepts and instances in WordNet. In Proceedings of the first global WordNet conference Mysore India.

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. What’s in a name? A large-scale computational study on how competition between names affects naming variation;Journal of Memory and Language;2023-12

2. The Aesthetic Emotion Lexicon: A Literature Review of Emotion Words Used by Researchers to Describe Aesthetic Experiences;Empirical Studies of the Arts;2023-03-13

3. When do languages use the same word for different meanings? The Goldilocks principle in colexification;Cognition;2022-09

4. Exploring the Representations of Individual Entities in the Brain Combining EEG and Distributional Semantics;Frontiers in Artificial Intelligence;2022-02-23