標題: Titlebook: Computational Intelligence in Data Science; 7th IFIP TC 12 Inter Mieczyslaw Lech Owoc,Felix Enigo Varghese Sicily,P Conference proceedings [打印本頁] 作者: panache 時間: 2025-3-21 19:31
書目名稱Computational Intelligence in Data Science影響因子(影響力)
書目名稱Computational Intelligence in Data Science影響因子(影響力)學科排名
書目名稱Computational Intelligence in Data Science網(wǎng)絡公開度
書目名稱Computational Intelligence in Data Science網(wǎng)絡公開度學科排名
書目名稱Computational Intelligence in Data Science被引頻次
書目名稱Computational Intelligence in Data Science被引頻次學科排名
書目名稱Computational Intelligence in Data Science年度引用
書目名稱Computational Intelligence in Data Science年度引用學科排名
書目名稱Computational Intelligence in Data Science讀者反饋
書目名稱Computational Intelligence in Data Science讀者反饋學科排名
作者: Indolent 時間: 2025-3-21 21:15
Chat Bot in Banking Sector Using Machine Learning and Natural Language ProcessingThe chat bot has advance machine learning algorithms and natural processing language to adapt for different queries and improve its performance in future and ensuring the perfect accuracy level of the answers. The system is combined with bank database so customers can see their bank details, ensurin作者: 商議 時間: 2025-3-22 03:35 作者: 隱士 時間: 2025-3-22 05:23 作者: 語言學 時間: 2025-3-22 10:03
Improved Evaluator for Subjective Answers Using Natural Language Processinguts like the user response, expected sentences and expected keywords and works with the help of numerical vectors, natural language processing and deep learning approaches and other mathematical calculations to calculate the aggregate score for an answer.作者: Harrowing 時間: 2025-3-22 14:24
Self-harm Detection from Texts: A Comparative Study Utilizing BERT, Machine Learning, and Deep Learnhese experiments, we attained exceptional F1 scores of 99% for RoBERTa, 98% for AlBERT, and 96% for BERT base. In contrast, traditional models like Logistic Regression achieved 93%, Random Forest 89%, and deep learning models such as LSTM, BiLSTM and CNN achieved 82%, 93% and 90%, respectively. The 作者: Harrowing 時間: 2025-3-22 21:06 作者: 個人長篇演說 時間: 2025-3-22 23:51 作者: 引水渠 時間: 2025-3-23 03:28 作者: opalescence 時間: 2025-3-23 09:11 作者: Critical 時間: 2025-3-23 11:57 作者: jeopardize 時間: 2025-3-23 15:31
Mieczyslaw Lech Owoc,Felix Enigo Varghese Sicily,P作者: isotope 時間: 2025-3-23 18:44 作者: 黃瓜 時間: 2025-3-24 00:13 作者: 索賠 時間: 2025-3-24 05:34
https://doi.org/10.1007/978-3-658-27431-3 techniques. Designed for open-source collaboration, this solution is positioned for continuous improvement, adaptation to evolving needs, and addressing emerging challenges in the field of intelligent transportation and related domains. This paper represents a foundational step towards establishing作者: 組成 時間: 2025-3-24 08:09
Arbeitsbereich Baumanagement – ic regression, SVM, stochastic gradient descent, decision trees, and ensemble models were conducted. In summary, this research contributes significantly to the ongoing battle against online toxicity and the promotion of more constructive online conversations. The RNN algorithm’s 99.47% accuracy rate作者: semiskilled 時間: 2025-3-24 13:34 作者: 廣大 時間: 2025-3-24 15:45
Die digitale Demokratie in der Schweizhese experiments, we attained exceptional F1 scores of 99% for RoBERTa, 98% for AlBERT, and 96% for BERT base. In contrast, traditional models like Logistic Regression achieved 93%, Random Forest 89%, and deep learning models such as LSTM, BiLSTM and CNN achieved 82%, 93% and 90%, respectively. The 作者: 進步 時間: 2025-3-24 19:32 作者: 綠州 時間: 2025-3-25 01:57
Julian Bubel Dipl.-Ing.,Jürgen Grabend reduce complexity. This is leading to improved classification performance. The proposed work is evaluated on six machine-learning models. The features extracted achieving a consistent AUC-ROC score of 95%. The highest accuracy of 95% on the Cleveland dataset. Our proposed machine learning-based C作者: 表主動 時間: 2025-3-25 04:57 作者: 證實 時間: 2025-3-25 10:40 作者: 兒童 時間: 2025-3-25 12:04 作者: 不能仁慈 時間: 2025-3-25 17:40 作者: 細節(jié) 時間: 2025-3-25 21:35
Analyzing the Computational Efficiency of LLM Models for NLP Tweet Classification During Emergency-CLSTM, and DistilBERT are four different NLP models that have been trained and tested. The findings will indicate the highest classification accuracy for determining if a tweet is informative or not. Our findings reveal that DistilBERT achieved the highest accuracy of 92.0% in testing and 89% in precision of the Twitter dataset.作者: 微塵 時間: 2025-3-26 01:45
Sentiment Analysis for Stock Prediction Using Mass Media Sourcesntial fluctuations in the stock prices of the target companies. This holistic approach capitalizes on the amalgamation of Natural language processing which combined with machine learning techniques, and real-time news data, delivering invaluable insights for both investors and traders.作者: 聽寫 時間: 2025-3-26 05:19 作者: 剛開始 時間: 2025-3-26 09:19
Conference proceedings 2024Intelligence in Data Science, ICCIDS 2024, held in Chennai, India, during February 21–23, 2024...The 63 full papers and 9 short papers presented in these proceedings were carefully reviewed and selected from 259 submissions.?The conference papers are organized in following topical sections:..Part I:作者: incite 時間: 2025-3-26 13:48 作者: Cacophonous 時間: 2025-3-26 17:49
Aktuelle Entwicklungen zum E-Governmentnd mutation processes, uncovering the most effective configurations for text generation. This evolutionary process is designed to yield an LSTM network architecture with enhanced performance in text generation.作者: 雕鏤 時間: 2025-3-26 21:10 作者: Breach 時間: 2025-3-27 01:50 作者: 痛恨 時間: 2025-3-27 07:27
Evaluating the?Language Translation Accuracy of?GPT-3.5 Using Prompt Engineeringreveals that carefully crafted prompts can significantly enhance the quality of GPT-3.5 translations, demonstrating the promising potential of this approach for boosting machine translation performance.作者: Encephalitis 時間: 2025-3-27 10:59
Neuro-Evolution-Based Language Model for?Text Generationnd mutation processes, uncovering the most effective configurations for text generation. This evolutionary process is designed to yield an LSTM network architecture with enhanced performance in text generation.作者: 憤世嫉俗者 時間: 2025-3-27 14:02 作者: HUMP 時間: 2025-3-27 20:57 作者: CLOUT 時間: 2025-3-28 01:00
Conference proceedings 2024 Applications of AI/ML in Natural Language Processing; and Applications of AI/ML in Image Processing...Part II: Applications of AI/ML in KDM, Cloud Computing & Security; Data Analytics;.?.and?Applications of ML..作者: WAIL 時間: 2025-3-28 04:24 作者: pacifist 時間: 2025-3-28 08:31 作者: Headstrong 時間: 2025-3-28 12:12 作者: 凝乳 時間: 2025-3-28 15:52
Chat Bot in Banking Sector Using Machine Learning and Natural Language Processingy also increased in these modern days. This research paper says about the design, development, various kind of chat bots present in now a days and how these chat bots are implemented and in which way it works according to customer queries. Chatbots are actually created to give accurate answers for b作者: jaunty 時間: 2025-3-28 20:35 作者: 魅力 時間: 2025-3-29 02:21
Multi-camera Enhanced Real-Time Content-Aware Vehicle Detectionimulation environments. The system transcends traditional vehicle detection, offering a comprehensive framework that includes object classification, precise location, and rotation estimation. Leveraging a multi-camera setup, our approach provides a comprehensive understanding of the surrounding envi作者: arousal 時間: 2025-3-29 06:24 作者: LEERY 時間: 2025-3-29 10:15 作者: Arthr- 時間: 2025-3-29 14:22
Self-harm Detection from Texts: A Comparative Study Utilizing BERT, Machine Learning, and Deep Learnma, leads to untreated issues, including self-harm and suicide. Social media has become a platform for expressing mental health concerns, and employing suitable algorithms enables automated suicide sentiment detection. This research compares various BERT models to identify an efficient approach for 作者: 歡騰 時間: 2025-3-29 15:46
Neuro-Evolution-Based Language Model for?Text Generationte architectures and substantial parameters of contemporary neural networks. This study introduces a groundbreaking method that applies Genetic Algorithms to evolve the architecture of Long Short-Term Memory networks (LSTM), specifically tailored for text generation tasks. Our approach employs a sop作者: persistence 時間: 2025-3-29 19:57 作者: 宿醉 時間: 2025-3-30 03:29
User Story Based Automated Test Case Generation Using NLPs. The present software development life cycle prioritizes the adjustment to evolving client requirements across the different stages of project development, facilitated by Continuous Integration and Continuous Deployment. The process produces a substantial volume of data that can serve as a valuabl作者: 惰性氣體 時間: 2025-3-30 06:04 作者: 遺忘 時間: 2025-3-30 11:58 作者: 廚房里面 時間: 2025-3-30 14:05
CADFRA: Coronary Artery Disease Feature Reduction with?Autoencoder for?Optimistic and?Effective Clasde range of detection mechanisms such as angiography. It is frequently used to forecast cardiac diseases. However it is costly and requires skilled technician. Alternative to angiography, there is a necessary for developing the cost-effective, non-invasive methods. Such methods should reduce financi作者: Excitotoxin 時間: 2025-3-30 17:30
Machine Learning Based Alzheimer’s Disease Detection: A Comprehensive Approachnal cortex and hippocampus. Following that, it affects the areas of the cerebral cortex responsible for language, cognition, and social interaction. Several other regions of the brain get harmed at some time. Patients with Alzheimer’s disease gradually lose their capacity to function normally and go作者: essential-fats 時間: 2025-3-30 21:37 作者: Ledger 時間: 2025-3-31 02:49
