作者: DIS 時間: 2025-3-21 20:51 作者: motor-unit 時間: 2025-3-22 00:56
0302-9743 na, during December 17–18, 2023..The 9 full papers in this book were carefully reviewed and selected from 14 submissions. They are organized in topical sections as follows:?Cognitive Computing Technologies and Infrastructure, Cognitive Computing Applications, Sensing Intelligence, Cognitive Analysis作者: 令人發(fā)膩 時間: 2025-3-22 08:23
Conference proceedings 2024 December 17–18, 2023..The 9 full papers in this book were carefully reviewed and selected from 14 submissions. They are organized in topical sections as follows:?Cognitive Computing Technologies and Infrastructure, Cognitive Computing Applications, Sensing Intelligence, Cognitive Analysis, Mobile S作者: electrolyte 時間: 2025-3-22 12:16
High-Precision Detection of Suicidal Ideation on Social Media Using Bi-LSTM and BERT Models Random Forest, XGBoost, and Logistic Regression before transitioning to advanced deep learning models. The Bi-LSTM and BERT models emerged as top performers, achieving detection accuracies of 97% and 98%, respectively. While our study is constrained by dataset limitations and potential biases, it m作者: echnic 時間: 2025-3-22 15:47 作者: echnic 時間: 2025-3-22 17:07
ENER: Named Entity Recognition Model for Ethnic Ancient Books Based on Entity Boundary Detectionries and generates the named entity tag sequence of ancient books. Experiments on the corpus of ancient books named entities and other general Chinese data sets show the effectiveness of our approach. On the one hand, ENER has improved the accuracy, recall and F1 value by 2.09%, 1.62% and 1.85% resp作者: 紅腫 時間: 2025-3-23 01:10
An Enhanced Opposition-Based Golden-Sine Whale Optimization Algorithmefined initial population. Furthermore, we introduce the Golden Sine Algorithm to modify the optimization approach of WOA, fostering an equilibrium between global exploration and exploitation abilities. In our evaluation, the proposed algorithm is assessed on nine classic benchmark functions with a 作者: DEAWL 時間: 2025-3-23 03:33
T4S: Two-Stage Screenplay Synopsis Summary Generation with?Turning PointsLM, rewrites key scene text and concatenates it to form the final plot summary of the movie script. The results of the implementation show that the proposed method in this paper outperforms baseline methods.作者: dyspareunia 時間: 2025-3-23 07:20
Multi-Factor Water Level Prediction Based on IndRNN-Attentionof specific historical moments for water level prediction. Experimental results demonstrate the effectiveness of our proposed method. Besides, the findings of this paper have practical implications for industry supervisors and cargo-carrying ships, providing scientific guidance for precise ship pre-作者: 去掉 時間: 2025-3-23 10:42 作者: 歡樂中國 時間: 2025-3-23 17:23 作者: MAIZE 時間: 2025-3-23 19:59
P-Reader: A Clue-Inspired Model for?Machine Reading Comprehension作者: NEG 時間: 2025-3-24 01:01 作者: 絆住 時間: 2025-3-24 04:01 作者: semble 時間: 2025-3-24 10:19 作者: 有幫助 時間: 2025-3-24 11:02
https://doi.org/10.1007/978-1-349-14899-8efined initial population. Furthermore, we introduce the Golden Sine Algorithm to modify the optimization approach of WOA, fostering an equilibrium between global exploration and exploitation abilities. In our evaluation, the proposed algorithm is assessed on nine classic benchmark functions with a 作者: Ingenuity 時間: 2025-3-24 17:35
https://doi.org/10.1007/978-1-349-14899-8LM, rewrites key scene text and concatenates it to form the final plot summary of the movie script. The results of the implementation show that the proposed method in this paper outperforms baseline methods.作者: 尖 時間: 2025-3-24 19:26
Selection on Several Characters,of specific historical moments for water level prediction. Experimental results demonstrate the effectiveness of our proposed method. Besides, the findings of this paper have practical implications for industry supervisors and cargo-carrying ships, providing scientific guidance for precise ship pre-作者: commodity 時間: 2025-3-25 01:27 作者: 昏迷狀態(tài) 時間: 2025-3-25 07:13
https://doi.org/10.1007/978-1-4020-6370-1cs. For the explanation generation task, we design a multi-level approach that integrates user and item IDs, as well as rating information, as soft prompts into the pre-trained model to generate personalized explanations. Experimental results demonstrate that our model outperforms state-of-the-art b作者: cathartic 時間: 2025-3-25 09:27 作者: 泥瓦匠 時間: 2025-3-25 12:03
978-3-031-51670-2The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl作者: 懲罰 時間: 2025-3-25 16:04 作者: FAWN 時間: 2025-3-25 22:08 作者: capsaicin 時間: 2025-3-26 03:00 作者: gusher 時間: 2025-3-26 06:44 作者: 兇兆 時間: 2025-3-26 09:08
https://doi.org/10.1007/978-1-349-14899-8e primary solutions for dealing with information overload and pinpointing key information. Unlike narrative text, movie scripts consist of sequences of scene descriptions, and directly compressing the text may lead to truncation of plot-relevant content. Furthermore, movie script summarization tasks作者: defibrillator 時間: 2025-3-26 15:11 作者: Badger 時間: 2025-3-26 20:19 作者: expdient 時間: 2025-3-26 23:57 作者: 一再煩擾 時間: 2025-3-27 04:27 作者: 索賠 時間: 2025-3-27 08:49 作者: Brocas-Area 時間: 2025-3-27 11:36 作者: cinder 時間: 2025-3-27 15:55 作者: 有權威 時間: 2025-3-27 20:30 作者: Ptosis 時間: 2025-3-27 22:16
An Enhanced Opposition-Based Golden-Sine Whale Optimization Algorithmaracterized by its simple structure, limited parameters, high efficiency, and robust optimization capacity, WOA has been extensively applied across multiple domains to address various challenges. Nonetheless, it has been found that the algorithm demonstrates low global exploration capability, inadeq作者: LAST 時間: 2025-3-28 02:47 作者: 喪失 時間: 2025-3-28 07:31
Multi-Factor Water Level Prediction Based on IndRNN-Attentioncrucial role in detecting water transfers. Existing water level prediction methods usually only consider a single factor (such as the historical water level data), and do not fully consider other factors such as flows from the upstream stations that affect the water level. To address this problem, i作者: 值得贊賞 時間: 2025-3-28 13:01 作者: 水獺 時間: 2025-3-28 18:31
Prompt Tuning Models on Sentiment-Aware for Explainable Recommendationions. However, most explainable recommendation methods only consider one aspect of sentiment in the reviews and lack sufficient exploration of the review texts. Besides, these methods often rely on deep neural networks and do not adequately consider how to effectively integrate extracted information作者: Anticlimax 時間: 2025-3-28 19:44
10樓作者: 尖酸一點 時間: 2025-3-28 23:45
10樓作者: 解脫 時間: 2025-3-29 04:47
10樓作者: BLANC 時間: 2025-3-29 11:01
10樓
