Results 31 to 40 of about 10,485,189 (358)
Multi-mode deep auto-encoder recommendation model for fusion of text information
Xi'an Gongcheng Daxue xuebao, 2021 A new recommendation model is proposed to solve the problems of data sparsity and deep semantic information learning when using score information as auxiliary recommendation.
Jinguang CHEN, Xinyi XU, Ganglong FAN
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Micron-BERT: BERT-Based Facial Micro-Expression Recognition
2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023 Micro-expression recognition is one of the most challenging topics in affective computing. It aims to recognize tiny facial movements difficult for humans to perceive in a brief period, i.e., 0.25 to 0.5 seconds. Recent advances in pre-training deep Bidirectional Transformers (BERT) have significantly improved self-supervised learning tasks in computer
Nguyen, Xuan-Bac +5 more
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LogBERT: Log Anomaly Detection via BERT [PDF]
IEEE International Joint Conference on Neural Network, 2021 Detecting anomalous events in online computer systems is crucial to protect the systems from malicious attacks or malfunctions. System logs, which record detailed information of computational events, are widely used for system status analysis.
Haixuan Guo, Shuhan Yuan, Xintao Wu
semanticscholar +1 more source
Catchment-scale dissolved carbon concentrations and export estimates across six subarctic streams in northern Sweden [PDF]
Biogeosciences, 2014 Climatic change is currently enhancing permafrost thawing and the flow of water through the landscape in subarctic and arctic catchments, with major consequences for the carbon export to aquatic ecosystems.
R. Giesler +7 more
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AUBER: Automated BERT regularization
PLOS ONE, 2021 How can we effectively regularize BERT? Although BERT proves its effectiveness in various NLP tasks, it often overfits when there are only a small number of training instances. A promising direction to regularize BERT is based on pruning its attention heads with a proxy score for head importance. However, these methods are usually suboptimal since they
Hyun Dong Lee, Seongmin Lee, U. Kang
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BERT-CoQAC: BERT-Based Conversational Question Answering in Context [PDF]
, 2021 As one promising way to inquire about any particular information through a dialog with the bot, question answering dialog systems have gained increasing research interests recently. Designing interactive QA systems has always been a challenging task in natural language processing and used as a benchmark to evaluate a machine's ability of natural ...
Zaib, Munazza +5 more
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Classification of Russian Texts by Genres Based on Modern Embeddings and Rhythm
Моделирование и анализ информационных систем, 2022 The article investigates modern vector text models for solving the problem of genre classification of Russian-language texts. Models include ELMo embeddings, BERT language model with pre-training and a complex of numerical rhythm features based on lexico-
Ksenia Vladimirovna Lagutina
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IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 2021 Someone's opinion on a product or service that is poured through a review is something that is quite important for the owner or potential customer. However, the large number of reviews makes it difficult for them to analyze the information contained in ...
Putri Rizki Amalia, Edi Winarko
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Connection Science, 2022 Aspect-level sentiment classification, a significant task of fine-grained sentiment analysis, aims to identify the sentimental information expressed in each aspect of a given sentence The existing methods combine global features and local structures to ...
Subo Wei +4 more
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ParsBERT: Transformer-based Model for Persian Language Understanding
, 2020 The surge of pre-trained language models has begun a new era in the field of Natural Language Processing (NLP) by allowing us to build powerful language models.
Farahani, Marzieh +3 more
core +1 more source