Results 41 to 50 of about 24,198 (261)
Aspect Extraction of Case Microblog Based on Double Embedded Convolutional Neural Network [PDF]
Jisuanji kexue, 2021 Aspect extraction of the microblog involved in the case is a task in a specific domain.The expression of aspect words is diverse and the meaning is different from that of the general domain.Only relying on the word embedding in the general domain,these ...
WANG Xiao-han, TAN Chen-chen, XIANG Yan, YU Zheng-tao
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Word Embedding With Zipf’s Context
IEEE Access, 2019 Word embeddings generated by neural language models have achieved great success in many NLP tasks. However, neural language models may be difficult to train and time consuming.
Lizheng Gao +3 more
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Unsupervised Word Embedding Learning by Incorporating Local and Global Contexts
Frontiers in Big Data, 2020 Word embedding has benefited a broad spectrum of text analysis tasks by learning distributed word representations to encode word semantics. Word representations are typically learned by modeling local contexts of words, assuming that words sharing ...
Yu Meng +5 more
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Comparative Analysis of Using Word Embedding in Deep Learning for Text Classification
Jurnal Riset Informatika, 2023 A group of theory-driven computing techniques known as natural language processing (NLP) are used to interpret and represent human discourse automatically.
Mukhamad Rizal Ilham, Arif Dwi Laksito
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Towards Resolving Word Ambiguity with Word Embeddings
CoRR, 2023 Ambiguity is ubiquitous in natural language. Resolving ambiguous meanings is especially important in information retrieval tasks. While word embeddings carry semantic information, they fail to handle ambiguity well. Transformer models have been shown to handle word ambiguity for complex queries, but they cannot be used to identify ambiguous words, e.g.
Matthias Thurnbauer +3 more
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Citation Intent Classification Using Word Embedding
IEEE Access, 2021 Citation analysis is an active area of research for various reasons. So far, statistical approaches are mainly used for citation analysis, which does not look into the internal context of the citations.
Muhammad Roman +4 more
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Compressing Word Embeddings [PDF]
, 2016 10 pages, 0 figures, submitted to ICONIP-2016. Previous experimental results were submitted to ICLR-2016, but the paper has been significantly updated, since a new experimental set-up worked much ...
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The activation of embedded words in spoken word recognition [PDF]
Journal of Memory and Language, 2015 The current study investigated how listeners understand English words that have shorter words embedded in them. A series of auditory-auditory priming experiments assessed the activation of six types of embedded words (2 embedded positions × 3 embedded proportions) under different listening conditions.
Xujin, Zhang, Arthur G, Samuel
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Overcoming Poor Word Embeddings with Word Definitions [PDF]
Proceedings of *SEM 2021: The Tenth Joint Conference on Lexical and Computational Semantics, 2021 Modern natural language understanding models depend on pretrained subword embeddings, but applications may need to reason about words that were never or rarely seen during pretraining. We show that examples that depend critically on a rarer word are more challenging for natural language inference models.
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Early Impact of Childhood Opportunity on Neurocognitive Outcomes in Sickle Cell Disease
Pediatric Blood &Cancer, EarlyView.ABSTRACT Introduction Neurocognitive impairment is a well‐recognized complication of sickle cell disease (SCD) that begins early in childhood and persists across development. While cerebrovascular injury contributes substantially to risk, neurocognitive deficits are also observed in children without overt or silent cerebral infarctions, suggesting ...
Julia E. LaMotte +5 more
wiley +1 more source