Dimensionality Reduction in Handwritten Digit Recognition

Lecture notes in networks and systems, Год журнала: 2023, Номер unknown, С. 35 - 50

Опубликована: Янв. 1, 2023

Язык: Английский

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Arabic Chatbot Evaluation Based on Extractive Question-Answering Transfer Learning and Language Transformers

Опубликована: Июль 11, 2023

Chatbots are computer programs that use artificial intelligence to imitate human conversations. Recent advancements in deep learning have shown interest utilizing language transformers, which do not rely on predefined rules and responses like traditional chatbots. This study provides a comprehensive review of previous research chatbots employ transfer models. Specifically, it examines the current trends using transformers with techniques evaluate ability Arabic understand conversation context demonstrate natural behavior. The proposed methods explore AraBERT, CAMeLBERT, AraElectra-SQuAD, AraElectra (Generator/Discriminator) different variants these semantic embedding Two datasets were used for evaluation: one 398 questions corresponding documents, another 1395 365,568 documents sourced from Wikipedia. Extensive experimental works conducted, evaluating both manually crafted entire set questions, confidence similarity metrics. results showed AraElectra-SQuAD model achieved an average score 0.6422 0.9773 first dataset, 0.6658 0.9660 second dataset. concludes consistently outperformed other models, displaying remarkable performance, high confidence, scores, as well robustness, highlighting its potential practical applications processing tasks suggests can be further enhanced applied various such chatbots, virtual assistants, information retrieval systems Arabic-speaking users. By combining power transformer architecture fine-tuning SQuAD-like large data, this trend demonstrates provide accurate contextually relevant answers Arabic.

Язык: Английский

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Accurate Prediction of Lysine Methylation Sites Using Evolutionary and Structural-Based Information

Cognitive Computation, Год журнала: 2024, Номер 16(3), С. 1300 - 1320

Опубликована: Май 1, 2024

Abstract Methylation is considered one of the proteins’ most important post-translational modifications (PTM). Plasticity and cellular dynamics are among many traits that regulated by methylation. Currently, methylation sites identified using experimental approaches. However, these methods time-consuming expensive. With use computer modelling, can be quickly accurately, providing valuable information for further trial investigation. In this study, we propose a new machine-learning model called MeSEP to predict incorporates both evolutionary structural-based information. To build model, first extract structural features from PSSM SPD2 profiles, respectively. We then employ Extreme Gradient Boosting (XGBoost) as classification sites. address issue imbalanced data bias towards negative samples, SMOTETomek-based hybrid sampling method. The was validated on an independent test set (ITS) 10-fold cross-validation (TCV) lysine method achieved: accuracy 82.9% in ITS 84.6% TCV; precision 0.92 0.94 area under curve values 0.90 F1 score 0.81 0.83 MCC 0.67 0.70 TCV. significantly outperformed previous studies found literature. standalone toolkit all its source codes publicly available at https://github.com/arafatro/MeSEP .

Язык: Английский

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Classification of Cancer Types Based on RNA HI-SEQ Data Using Dimensionality Reduction

Communications in computer and information science, Год журнала: 2024, Номер unknown, С. 309 - 324

Опубликована: Янв. 1, 2024

Язык: Английский

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Mental Health Chatbot

Опубликована: Июнь 21, 2024

Язык: Английский

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Using Ontology to Analyze English Comments on Social Networks

Informatics and Automation, Год журнала: 2024, Номер 23(5), С. 1311 - 1338

Опубликована: Сен. 25, 2024

Chatbots have become interesting for many users as technology becomes more and advanced. The need information exchange among people through computer systems is increasing daily, raising the preference using chatbots in most countries. Since Vietnam such a developing country with variety of ethnic groups, it requires much attention to proliferation social networks expansion cooperative economy. Regarding networks, inappropriate use words everyday life has significant issue. There are mixed reviews praise criticism on networks; we try reduce negative language improve quality language. We aim meet users’ needs promote economic development, address issues effectively. To achieve these goals, this paper propose deep learning technique ontology knowledge mining collect process comments networks. This approach aims enhance user experience facilitate by opinions comments. Experimental results demonstrate that our method outperforms conventional approach.

Язык: Английский

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Peran Chatbot dalam Menangani Masalah Kesehatan Mental selama Pandemi COVID-19: Tinjauan Mini

Bincang Sains dan Teknologi, Год журнала: 2022, Номер 1(01), С. 1 - 11

Опубликована: Авг. 3, 2022

Pada artikel ini, kami menyajikan ulasan mini tentang potensi chatbot untuk memerangi masalah kesehatan mental selama pandemi COVID-19. Kami perbandingan studi terdahulu terkait COVID-19 dan pengembangan chatbot. juga melakukan survei memberikan wawasan bagaimana orang memandang sebagai bantuan mereka. Naskah ini bertujuan gambaran kemungkinan mengurangi penyakit mental. Ada beberapa hal yang perlu diperhatikan secara serius dalam mengembangkan dukungan emosional, antara lain keamanan, perhatian privasi, paradigma etika. Namun, di referensi menarik, sebagian besar menunjukkan bahwa adalah alternatif baik mental, terutama

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Logistic Regression Approach to a Joint Classification and Feature Selection in Lung Cancer Screening Using CPRD Data

Lecture notes in networks and systems, Год журнала: 2023, Номер unknown, С. 191 - 206

Опубликована: Янв. 1, 2023

Язык: Английский

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A Nonparametric Model for Forecasting Life Expectancy at Birth Using Gaussian Process

Communications in computer and information science, Год журнала: 2022, Номер unknown, С. 102 - 116

Опубликована: Янв. 1, 2022

Язык: Английский

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Machine Learning Models to Analyze the Effect of Drugs on Neonatal-ICU Length of Stay

Communications in computer and information science, Год журнала: 2022, Номер unknown, С. 186 - 204

Опубликована: Янв. 1, 2022

Язык: Английский

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