Results 51 to 60 of about 96,400 (324)

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, Ran Feng, Xinyue Liu, Yuangang Li, Xianchao Zhang   +4 more
doaj   +1 more source

Gloss Alignment using Word Embeddings

2023 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW), 2023
Capturing and annotating Sign language datasets is a time consuming and costly process. Current datasets are orders of magnitude too small to successfully train unconstrained \acf{slt} models. As a result, research has turned to TV broadcast content as a source of large-scale training data, consisting of both the sign language interpreter and the ...
Walsh, Harry, Sincan, Ozge Mercanoglu, Saunders, Ben, Bowden, Richard   +3 more
openaire   +2 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, Hongjun Zhang, Wenning Hao, Kai Cheng, Guanglu Zhang   +4 more
doaj   +1 more source

Mimicking Word Embeddings using Subword RNNs

, 2017
Word embeddings improve generalization over lexical features by placing each word in a lower-dimensional space, using distributional information obtained from unlabeled data.
Eisenstein, Jacob, Guthrie, Robert, Pinter, Yuval   +2 more
core   +1 more source

Phonetic Word Embeddings

, 2021
This work presents a novel methodology for calculating the phonetic similarity between words taking motivation from the human perception of sounds. This metric is employed to learn a continuous vector embedding space that groups similar sounding words together and can be used for various downstream computational phonology tasks.
Sharma, Rahul, Dhawan, Kunal, Pailla, Balakrishna   +2 more
openaire   +2 more sources

Closed Form Word Embedding Alignment [PDF]

2019 IEEE International Conference on Data Mining (ICDM), 2019
We develop a family of techniques to align word embeddings which are derived from different source datasets or created using different mechanisms (e.g., GloVe or word2vec). Our methods are simple and have a closed form to optimally rotate, translate, and scale to minimize root mean squared errors or maximize the average cosine similarity between two ...
Sunipa Dev, Safia Hassan, Jeff M. Phillips   +2 more
openaire   +2 more sources

Comparing the Effect of Semi‐Immersive Virtual Reality, Computerized Cognitive Training, and Traditional Rehabilitation on Cognitive Function in Multiple Sclerosis: A Randomized Clinical Trial

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Cognitive impairment is a common non‐motor symptom in Multiple Sclerosis (MS), negatively affecting autonomy and Quality of Life (QoL). Innovative rehabilitation strategies, such as semi‐immersive virtual reality (VR) and computerized cognitive training (CCT), may offer advantages over traditional cognitive rehabilitation (TCR ...
Maria Grazia Maggio, Desiree Latella, Lilla Bonanno, Paulo Cezar Rocha dos Santos, Marcos Maldonado‐Díaz, Meir Plotnik, Rosaria De Luca, Angelo Quartarone, Rocco Salvatore Calabrò   +8 more
wiley   +1 more source

An accurate transformer-based model for transition-based dependency parsing of free word order languages

Journal of King Saud University: Computer and Information Sciences
Transformer 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, Khalid Saleem, Surayya Naz   +2 more
doaj   +1 more source

Quantum-Inspired Complex Word Embedding [PDF]

Proceedings of The Third Workshop on Representation Learning for NLP, 2018
A challenging task for word embeddings is to capture the emergent meaning or polarity of a combination of individual words. For example, existing approaches in word embeddings will assign high probabilities to the words "Penguin" and "Fly" if they frequently co-occur, but it fails to capture the fact that they occur in an opposite sense - Penguins do ...
Li, Qiuchi, Uprety, Sagar, Wang, Benyou, Song, Dawei   +3 more
openaire   +2 more sources

Integrating Patient‐Reported Quality Measures in Systemic Lupus Erythematosus: Development of the American College of Rheumatology Implementation Guide

Arthritis Care &Research, EarlyView.
Objective To support high‐quality, patient‐centered care for systemic lupus erythematosus (SLE), the American College of Rheumatology (ACR) developed evidence‐based measures incorporating clinical and patient‐reported outcome measures (PROMs). Using the Consolidated Framework for Implementation Research (CFIR), we conducted semistructured interviews ...
Catherine Nasrallah, Cherish Wilson, Christine Hariz, Christie M. Bartels, Shanthini Kasturi, Wambui Machua, Amy Bennett, Kate Chiseri, Allison Plitman, Starla Hairston Blanks, April Jorge, Patti Katz, Jinoos Yazdany, Shivani Garg   +13 more
wiley   +1 more source