Results 61 to 70 of about 1,006,138 (295)
GLTM: A Global and Local Word Embedding-Based Topic Model for Short Texts
IEEE Access, 2018 Short texts have become a kind of prevalent source of information, and discovering topical information from short text collections is valuable for many applications.
Wenxin Liang +4 more
doaj +1 more source
, 2019 [Plan TL/medicine/word embeddings] Word embeddings generated from Spanish corpora that includes: (a) the full-text in Spanish available in Scielo.org (until December/2018), (b) all articles from the following Wikipedia categories: Pharmacology, Pharmacy,
Aitor Gonzalez-Agirre +9 more
core +1 more source
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
openaire +3 more sources
Compositional Demographic Word Embeddings [PDF]
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2020 Word embeddings are usually derived from corpora containing text from many individuals, thus leading to general purpose representations rather than individually personalized representations. While personalized embeddings can be useful to improve language model performance and other language processing tasks, they can only be computed for people with a ...
Charles Welch +3 more
openaire +3 more sources
Learning Chinese Word Embeddings With Words and Subcharacter N-Grams
IEEE Access, 2019 Co-occurrence information between words is the basis of training word embeddings; besides, Chinese characters are composed of subcharacters, words made up by the same characters or subcharacters usually have similar semantics, but this internal ...
Ruizhi Kang +4 more
doaj +1 more source
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
openaire +2 more sources
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.
openaire +3 more sources
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background The Standards for Psychosocial Care for Children with Cancer and Their Families guide the provision of comprehensive psychosocial care. Parallel to research characterizing implementation of the Standards from the perspective of providers, this study examines implementation of the Standards from the perspective of parents of youth ...
Emily M. Pariseau +8 more
wiley +1 more source
Journal of King Saud University: Computer and Information SciencesTransformer models are the state-of-the-art in Natural Language Processing (NLP) and the core of the Large Language Models (LLMs). We propose a transformer-based model for transition-based dependency parsing of free word order languages.
Fatima Tuz Zuhra +2 more
doaj +1 more source