Results 51 to 60 of about 24,198 (261)
Future Internet, 2018 Chinese event extraction uses word embedding to capture similarity, but suffers when handling previously unseen or rare words. From the test, we know that characters may provide some information that we cannot obtain in words, so we propose a novel ...
Yue Wu, Junyi Zhang
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Improving Word Embedding Using Variational Dropout
Proceedings of the International Florida Artificial Intelligence Research Society Conference, 2023 Pre-trained word embeddings are essential in natural language processing (NLP). In recent years, many post-processing algorithms have been proposed to improve the pre-trained word embeddings.
Zainab Albujasim +3 more
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Biomedical Word Sense Disambiguation with Word Embeddings [PDF]
, 2017 There is a growing need for automatic extraction of information and knowledge from the increasing amount of biomedical and clinical data produced, namely in textual form. Natural language processing comes in this direction, helping in tasks such as information extraction and information retrieval.
Rui Antunes 0002, Sérgio Matos
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Adaptive Compression of Word Embeddings [PDF]
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020 Distributed representations of words have been an indispensable component for natural language processing (NLP) tasks. However, the large memory footprint of word embeddings makes it challenging to deploy NLP models to memory-constrained devices (e.g., self-driving cars, mobile devices).
Yeachan Kim +2 more
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Neuroblastoma's complex, heterogeneous biology poses significant diagnostic and therapeutic challenges, often requiring caregivers to absorb complex information and participate in time‐sensitive decisions. However, caregivers often feel unprepared to evaluate options.
Vickie Buenger +8 more
wiley +1 more source
FEBS Letters, EarlyView.Embryo‐like structures (stembryos) are an innovative tool, but they are hindered by experimental variability and limited developmental potential. DNA methylation is crucial for mammalian development, but its status in stembryo models is poorly characterized.
Sara Canil +4 more
wiley +1 more source
A Smaller and Better Word Embedding for Neural Machine Translation
IEEE Access, 2023 Word embeddings play an important role in Neural Machine Translation (NMT). However, it still has a series of problems such as ignoring the prior knowledge of the association between words, relying on specific task constraints passively in parameter ...
Qi Chen
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Spoken-Word Recognition: The Access to Embedded Words
Brain and Language, 1999 Two cross-modal priming experiments investigated whether the representation of either an initial- or a final-embedded word may be activated when the longer carrier word is auditorily presented. Visual targets were semantically related either to the embedded word or to the carrier word or they were unrelated to the primes. A priming effect was found for
Isel, F., Bacri, N.
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A Joint Model for Word Embedding and Word Morphology [PDF]
Proceedings of the 1st Workshop on Representation Learning for NLP, 2016 This paper presents a joint model for performing unsupervised morphological analysis on words, and learning a character-level composition function from morphemes to word embeddings. Our model splits individual words into segments, and weights each segment according to its ability to predict context words.
Rei, Marek, Cao, Kris
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New Directions for Adult and Continuing Education, EarlyView.ABSTRACT Mental well‐being is central to adult learner success, yet many adult education institutions lack capacity to provide timely and accessible support. This article examines how artificial intelligence (AI) can strengthen mental health–adjacent supports in adult and continuing higher education, with attention to professional practice and ...
Adam L. McClain, Thomas Wade
wiley +1 more source