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1
A Computational Model of Comprehension in Manga Style Visual Narratives
In: Proceedings of the Annual Meeting of the Cognitive Science Society, vol 43, iss 43 (2021)
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2
音樂教學協助國小學童多元智能表現之探究 ; A Study of Elementary School Students’ Multiple Intelligence Performance Assisted in Music Teaching Program
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3
臺灣大學生學習英語的動機與使用英語溝通的意願之間的關係 ; The Relationship between Taiwanese EFL Students’ Motivation and Willingness to Communicate
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4
Breaking Down Multilingual Machine Translation ...
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5
An Empirical Study on Multiple Information Sources for Zero-Shot Fine-Grained Entity Typing ...
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6
Adversary-Aware Rumor Detection ...
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7
A Computational Model of Comprehension in Manga Style Visual Narratives ...
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8
A Computational Model of Comprehension in Manga Style Visual Narratives ...
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9
Integrated Semantic and Phonetic Post-correction for Chinese Speech Recognition ...
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10
Amis-Chinese CS ...
Chen, Yi-Ting. - : Zenodo, 2021
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11
Amis-Chinese CS ...
Chen, Yi-Ting. - : Zenodo, 2021
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12
Bilateral cerebral infarction in diabetic ketoacidosis and bilateral internal carotid artery occlusion: A case report and review of literature
In: World J Clin Cases (2021)
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13
Linguistic Patterns for Code Word Resilient Hate Speech Identification
In: Sensors (Basel) (2021)
Abstract: The permanent transition to online activity has brought with it a surge in hate speech discourse. This has prompted increased calls for automatic detection methods, most of which currently rely on a dictionary of hate speech words, and supervised classification. This approach often falls short when dealing with newer words and phrases produced by online extremist communities. These code words are used with the aim of evading automatic detection by systems. Code words are frequently used and have benign meanings in regular discourse, for instance, “skypes, googles, bing, yahoos” are all examples of words that have a hidden hate speech meaning. Such overlap presents a challenge to the traditional keyword approach of collecting data that is specific to hate speech. In this work, we first introduced a word embedding model that learns the hidden hate speech meaning of words. With this insight on code words, we developed a classifier that leverages linguistic patterns to reduce the impact of individual words. The proposed method was evaluated across three different datasets to test its generalizability. The empirical results show that the linguistic patterns approach outperforms the baselines and enables further analysis on hate speech expressions.
Keyword: Article
URL: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8659976/
https://doi.org/10.3390/s21237859
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14
Human Being Ecology in Richard Powers’ Generosity
In: Studies in Literature and Language; Vol 22, No 1 (2021): Studies in Literature and Language; 1-9 ; 1923-1563 ; 1923-1555 (2021)
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