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The role of object novelty and pragmatic reasoning in referent selection and word learning (Study 2b) ...
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MORPHOLOGICAL AND IDENTITY PRIMING IN WORD LEARNING AND TEXT READING AS A WINDOW INTO THE MENTAL LEXICON
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Data From: A Protracted Developmental Trajectory for English-Learning Children’s Detection of Consonant Mispronunciations in Newly Learned Words
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In: Speech and Hearing Sciences Faculty Datasets (2022)
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Xie, X., Liu, L., & Jaeger, T. F. (2021-JEP:G). Cross-talker generalization in the perception of non-nativespeech: a large-scale replication ...
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Preschool Children’s Processing of Events during Verb Learning: Is the Focus on People (Faces) or Their Actions (Hands)?
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In: Brain Sciences; Volume 12; Issue 3; Pages: 344 (2022)
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Analysis of the Effects of Lockdown on Staff and Students at Universities in Spain and Colombia Using Natural Language Processing Techniques
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In: International Journal of Environmental Research and Public Health; Volume 19; Issue 9; Pages: 5705 (2022)
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Deep Sentiment Analysis Using CNN-LSTM Architecture of English and Roman Urdu Text Shared in Social Media
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In: Applied Sciences; Volume 12; Issue 5; Pages: 2694 (2022)
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Vec2Dynamics: A Temporal Word Embedding Approach to Exploring the Dynamics of Scientific Keywords—Machine Learning as a Case Study
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In: Big Data and Cognitive Computing; Volume 6; Issue 1; Pages: 21 (2022)
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Abstract:
The study of the dynamics or the progress of science has been widely explored with descriptive and statistical analyses. Also this study has attracted several computational approaches that are labelled together as the Computational History of Science, especially with the rise of data science and the development of increasingly powerful computers. Among these approaches, some works have studied dynamism in scientific literature by employing text analysis techniques that rely on topic models to study the dynamics of research topics. Unlike topic models that do not delve deeper into the content of scientific publications, for the first time, this paper uses temporal word embeddings to automatically track the dynamics of scientific keywords over time. To this end, we propose Vec2Dynamics, a neural-based computational history approach that reports stability of k-nearest neighbors of scientific keywords over time; the stability indicates whether the keywords are taking new neighborhood due to evolution of scientific literature. To evaluate how Vec2Dynamics models such relationships in the domain of Machine Learning (ML), we constructed scientific corpora from the papers published in the Neural Information Processing Systems (NIPS; actually abbreviated NeurIPS) conference between 1987 and 2016. The descriptive analysis that we performed in this paper verify the efficacy of our proposed approach. In fact, we found a generally strong consistency between the obtained results and the Machine Learning timeline.
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Keyword:
computational linguistics; k -NN stability; machine learning; scientific literature; temporal word embedding
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URL: https://doi.org/10.3390/bdcc6010021
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Methods, Models and Tools for Improving the Quality of Textual Annotations
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In: Modelling; Volume 3; Issue 2; Pages: 224-242 (2022)
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TASE: Task-Aware Speech Enhancement for Wake-Up Word Detection in Voice Assistants
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In: Applied Sciences; Volume 12; Issue 4; Pages: 1974 (2022)
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Stimulus and response conflict from a second language: Stroop interference in weakly-bilingual and recently-trained languages
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In: ISSN: 0001-6918 ; EISSN: 1873-6297 ; Acta Psychologica ; https://hal.archives-ouvertes.fr/hal-03356475 ; Acta Psychologica, Elsevier, 2021, 218, pp.103360. ⟨10.1016/j.actpsy.2021.103360⟩ (2021)
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Variation in phonological bias: Bias for vowels, rather than consonants or tones in lexical processing by Cantonese-learning toddlers
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In: ISSN: 0010-0277 ; EISSN: 1873-7838 ; Cognition ; https://hal.archives-ouvertes.fr/hal-02997489 ; Cognition, Elsevier, 2021, 213, pp.104486. ⟨10.1016/j.cognition.2020.104486⟩ (2021)
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SCALa: A blueprint for computational models of language acquisition in social context
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In: ISSN: 0010-0277 ; EISSN: 1873-7838 ; Cognition ; https://hal.inria.fr/hal-03373586 ; Cognition, Elsevier, 2021, 213, pp.104779. ⟨10.1016/j.cognition.2021.104779⟩ (2021)
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Variation in phonological bias: Bias for vowels, rather than consonants or tones in lexical processing by Cantonese-learning toddlers
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In: ISSN: 0010-0277 ; EISSN: 1873-7838 ; Cognition ; https://hal.archives-ouvertes.fr/hal-03391035 ; Cognition, Elsevier, 2021, 213, pp.104486. ⟨10.1016/j.cognition.2020.104486⟩ (2021)
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Subjective confidence influences word learning in a cross-situational statistical learning task
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In: ISSN: 0749-596X ; EISSN: 1096-0821 ; Journal of Memory and Language ; https://hal.archives-ouvertes.fr/hal-03468212 ; Journal of Memory and Language, Elsevier, 2021, 121, pp.104277 (2021)
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Familiar words can serve as a semantic seed for syntactic bootstrapping
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In: ISSN: 1363-755X ; EISSN: 1467-7687 ; Developmental Science ; https://hal.archives-ouvertes.fr/hal-03098829 ; Developmental Science, Wiley, 2021, 24 (1), pp.e13010. ⟨10.1111/desc.13010⟩ (2021)
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