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Predicting human similarity judgments with distributional models: The value of word associations.
Simon De Deyne
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Amy Perfors
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Daniel J Navarro
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Paper Details:
Month: December
Year: 2016
Location: Osaka, Japan
Venue:
COLING |
Citations
URL
Recognizing Humour using Word Associations and Humour Anchor Extraction
Andrew Cattle
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Xiaojuan Ma
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Speaking, Seeing, Understanding: Correlating semantic models with conceptual representation in the brain
Luana Bulat
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Stephen Clark
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Ekaterina Shutova
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Predicting Word Association Strengths
Andrew Cattle
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Xiaojuan Ma
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Demographic-aware word associations
Aparna Garimella
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Carmen Banea
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Rada Mihalcea
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Associative Multichannel Autoencoder for Multimodal Word Representation
Shaonan Wang
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Jiajun Zhang
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Chengqing Zong
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Evaluation by Association: A Systematic Study of Quantitative Word Association Evaluation
Ivan Vulić
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Douwe Kiela
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Anna Korhonen
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Querying Word Embeddings for Similarity and Relatedness
Fatemeh Torabi Asr
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Robert Zinkov
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Michael Jones
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WordNet Embeddings
Chakaveh Saedi
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António Branco
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João António Rodrigues
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João Silva
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http://creativecommons.org/licenses/by/4.0/
https://smallworldofwords.org/
http://simondedeyne.me/data
http://zipf.ugent.be/snaut-downloads/spaces/english/predict/
https://levyomer.wordpress.com/2014/04/25/dependency-based-word-embeddings/
http://nlp.stanford.edu/projects/glove/
Field Of Study
Linguistic Trends
Distributional Semantics
Embeddings
Task
Semantic Similarity
Language
English
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