標(biāo)題: Titlebook: Database Systems for Advanced Applications; 26th International C Christian S. Jensen,Ee-Peng Lim,Chih-Ya Shen Conference proceedings 2021 T [打印本頁] 作者: 投降 時間: 2025-3-21 18:45
書目名稱Database Systems for Advanced Applications影響因子(影響力)
書目名稱Database Systems for Advanced Applications影響因子(影響力)學(xué)科排名
書目名稱Database Systems for Advanced Applications網(wǎng)絡(luò)公開度
書目名稱Database Systems for Advanced Applications網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Database Systems for Advanced Applications被引頻次
書目名稱Database Systems for Advanced Applications被引頻次學(xué)科排名
書目名稱Database Systems for Advanced Applications年度引用
書目名稱Database Systems for Advanced Applications年度引用學(xué)科排名
書目名稱Database Systems for Advanced Applications讀者反饋
書目名稱Database Systems for Advanced Applications讀者反饋學(xué)科排名
作者: 導(dǎo)師 時間: 2025-3-21 20:44
Stephen Nkansah Morgan,Beatrice Okyere-Manu any possible attack. Recently, although a certified method based on randomized smoothing is proposed, it does not take the maximized . into account, so we develop an approach to train models with maximized certified regions via replacing the base classifier with the soft smoothed classifier which is differentiable during propagation.作者: Ballerina 時間: 2025-3-22 03:36 作者: Interstellar 時間: 2025-3-22 08:32 作者: AROMA 時間: 2025-3-22 12:38 作者: 障礙物 時間: 2025-3-22 15:43 作者: 障礙物 時間: 2025-3-22 20:29
0302-9743 network, recommendation, graph, learning, and model. These topic areas and keywords shed the light on the direction where the research in DASFAA is moving towards...Due to the Corona pandemic this event was held virtually..978-3-030-73196-0978-3-030-73197-7Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: 精確 時間: 2025-3-22 22:18 作者: 媽媽不開心 時間: 2025-3-23 03:30 作者: fulmination 時間: 2025-3-23 06:31
Multi-label Classification of Long Text Based on Key-Sentences Extractionention mechanism to improve the efficiency of our model. Experimental results on real-world datasets demonstrate that our proposed model achieves significant and consistent improvements compared with other state-of-the-art baselines.作者: ALT 時間: 2025-3-23 12:01 作者: MEAN 時間: 2025-3-23 16:43 作者: 時代錯誤 時間: 2025-3-23 21:11 作者: cogent 時間: 2025-3-23 22:18 作者: 6Applepolish 時間: 2025-3-24 03:08 作者: ERUPT 時間: 2025-3-24 07:04
Unpaired Multimodal Neural Machine Translation via Reinforcement Learning learning process, i.e., (1) the likelihood of generated sentence given source image and (2) the distance of attention weights given by image caption models. Experimental results on the Multi30K, IAPR-TC12, and IKEA datasets show that the proposed learning mechanism achieves better performance than existing methods.作者: 南極 時間: 2025-3-24 11:09
Inferring Deterministic Regular Expression with Unorder and CountingC to a SOREUC by introducing unordered concatenations and counting operators. Experimental results demonstrate that, SOREUCs have stronger expressive powers for modeling unordered schemata than existing works, and our algorithm can efficiently infer a concise SOREUC with better generalization ability.作者: expdient 時間: 2025-3-24 18:18
Conference proceedings 2021 DASFAA 2021, held in Taipei, Taiwan, in April 2021...The total of 156 papers presented in this three-volume set was carefully reviewed and selected from 490 submissions...The topic areas for the selected papers include information retrieval, search and recommendation techniques; RDF, knowledge grap作者: 知識 時間: 2025-3-24 19:15 作者: 切割 時間: 2025-3-25 01:59
Hegel and the Negation of the ApophaticThus, our encoder could focus on important words and sentences in the input review. Then a summary decoder is employed to generate target summaries with hierarchical attention likewise, where the decoding scores are not only related to word information, but re-weighted by another sentence-level atte作者: 證明無罪 時間: 2025-3-25 06:00
Palgrave Frontiers in Philosophy of Religionchoosing key semantic vectors to guide the response generation. Based on the structured semantics, it also develops a calibration mechanism with a dynamic vocabulary during decoding, which enhances exact coherent expressions by adjusting word distribution. According to the experiments, ConDial shows作者: 迫擊炮 時間: 2025-3-25 08:34
Palgrave Frontiers in Philosophy of Religionrom refined word representations through fully connected layers. Moreover, we propose a triangle distance loss function for embedding layers as an auxiliary task to obtain discriminative representations. It is optimized jointly with pairwise ranking loss for ad hoc document ranking task. Experimenta作者: 松雞 時間: 2025-3-25 14:06
Zhongwei Zhao,Wei Chen,Yongai Jins (AAN) to learn the domain-invariant and discriminative features simultaneously based on Maximum Mean Discrepancy (MMD) and CMD. Meanwhile, to trade off between the marginal and conditional distributions, we further maximize both MMD and CMD criterions using adversarial strategy to make the feature作者: senile-dementia 時間: 2025-3-25 19:20 作者: 雜役 時間: 2025-3-25 22:02
Zhongwei Zhao,Wei Chen,Yongai Jinte-of-the-art filter methods for text feature selection and conduct experiments on two datasets: Reuters-21578 and WebKB. K-Nearest Neighbor (KNN) and Support Vector Machine (SVM) are taken as the subsequent classifiers. Experimental results shows that the proposed DMI has significantly improved the作者: Creatinine-Test 時間: 2025-3-26 00:10
Understanding Fertility Trends in China history questions and answers are encoded into the contexts for the multi-turn setting. To capture the task-level importance of different layer outputs, a task-specific attention layer is further added to the CAT-BERT outputs, reflecting the positions that the model should pay attention to for a sp作者: anarchist 時間: 2025-3-26 05:17
Silindiwe Zvingowanisei,Sophia Chirongomaration Search approach by Shared Structure encoding for neural-based Multi-Task models (TGG-S3MT). The experiments based on the real text datasets with multiple text mining tasks show that SSE is effective for formulating the multi-task architecture search. Moreover, both .-S4MT and TGG-S3MT have be作者: confide 時間: 2025-3-26 09:01 作者: 拾落穗 時間: 2025-3-26 15:54 作者: Badger 時間: 2025-3-26 17:19
Automated Context-Aware Phrase Mining from Text Corporaity phrases effectively. 2) an instance selection network that focuses on choosing correct sentences with reinforcement learning for further improving the prediction performance of phrase recognition network. Experimental results demonstrate that our ConPhrase outperforms the state-of-the-art approa作者: 漫不經(jīng)心 時間: 2025-3-26 23:11
Neural Adversarial Review Summarization with Hierarchical Personalized AttentionThus, our encoder could focus on important words and sentences in the input review. Then a summary decoder is employed to generate target summaries with hierarchical attention likewise, where the decoding scores are not only related to word information, but re-weighted by another sentence-level atte作者: Peak-Bone-Mass 時間: 2025-3-27 03:16 作者: Statins 時間: 2025-3-27 09:16 作者: Resection 時間: 2025-3-27 11:39 作者: 燒瓶 時間: 2025-3-27 15:27 作者: 同音 時間: 2025-3-27 18:17
Discriminant Mutual Information for Text Feature Selectionte-of-the-art filter methods for text feature selection and conduct experiments on two datasets: Reuters-21578 and WebKB. K-Nearest Neighbor (KNN) and Support Vector Machine (SVM) are taken as the subsequent classifiers. Experimental results shows that the proposed DMI has significantly improved the作者: 小臼 時間: 2025-3-28 00:31
CAT-BERT: A Context-Aware Transferable BERT Model for Multi-turn Machine Reading Comprehension history questions and answers are encoded into the contexts for the multi-turn setting. To capture the task-level importance of different layer outputs, a task-specific attention layer is further added to the CAT-BERT outputs, reflecting the positions that the model should pay attention to for a sp作者: 使人入神 時間: 2025-3-28 06:03 作者: 聽寫 時間: 2025-3-28 08:15 作者: 緩解 時間: 2025-3-28 13:45 作者: 深淵 時間: 2025-3-28 15:04
Multi-label Classification of Long Text Based on Key-Sentences Extractioned global feature information. Some approaches that split an entire text into multiple segments for feature extracting, which generates noise features of irrelevant segments. To address these issues, we introduce key-sentences extraction task with semi-supervised learning to quickly distinguish rele作者: Collected 時間: 2025-3-28 21:41
Automated Context-Aware Phrase Mining from Text Corporatext into structured information. Existing statistic-based methods have achieved the state-of-the-art performance of this task. However, such methods often heavily rely on statistical signals to extract quality phrases, ignoring the effect of ...In this paper, we propose a novel context-aware method作者: 全面 時間: 2025-3-28 23:48
Keyword-Aware Encoder for Abstractive Text Summarizationn summarizing a text. Fewer efforts are needed to write a high-quality summary if keywords in the original text are provided. Inspired by this observation, we propose a keyword-aware encoder (KAE) for abstractive text summarization, which extracts and exploits keywords explicitly. It enriches word r作者: 陪審團每個人 時間: 2025-3-29 05:04
Neural Adversarial Review Summarization with Hierarchical Personalized Attention and ignore different informativeness of different sentences in a review towards summary generation. In addition, the personalized information along with reviews (e.g., user/product and ratings) is also highly related to the quality of generated summaries. Hence, we propose a review summarization me作者: 妨礙 時間: 2025-3-29 09:35
Generating Contextually Coherent Responses by Learning Structured Vectorized Semanticso appropriately encode contexts and how to make good use of them during the generation. Past works either directly use (hierarchical) RNN to encode contexts or use attention-based variants to further weight different words and utterances. They tend to learn dispersed focuses over all contextual info作者: Legend 時間: 2025-3-29 12:28 作者: Feedback 時間: 2025-3-29 19:03 作者: angiography 時間: 2025-3-29 22:28 作者: 無法解釋 時間: 2025-3-30 00:33
Discriminant Mutual Information for Text Feature Selection because of high correlation between features; so, it is necessary to execute feature selection. In this paper, we propose a Discriminant Mutual Information (DMI) criterion to select features for text classification tasks. DMI measures the discriminant ability of features from two aspects. One is th作者: 畏縮 時間: 2025-3-30 04:13 作者: blackout 時間: 2025-3-30 11:57
Unpaired Multimodal Neural Machine Translation via Reinforcement Learning to collect. To tackle this problem, multimodal content, especially image, has been introduced to help build an NMT system without parallel corpora. In this paper, we propose a reinforcement learning (RL) method to build an NMT system by introducing a sequence-level supervision signal as a reward. B作者: Accord 時間: 2025-3-30 13:41
Multimodal Named Entity Recognition with Image Attributes and Image Knowledgety types. The existing efforts are often flawed in two aspects. Firstly, they may easily ignore the natural prejudice of visual guidance brought by the image. Secondly, they do not further explore the knowledge contained in the image. In this paper, we novelly propose a novel neural network model wh作者: 流出 時間: 2025-3-30 17:24 作者: Intersect 時間: 2025-3-30 21:57
A Semi-structured Data Classification Model with Integrating Tag Sequence and Ngramfication plays an important role in many data analysis applications. In addition to content information, semi-structured data also contain structural information. Thus, combining the structure and content features is a crucial issue in semi-structured data classification. In this paper, we propose a作者: mydriatic 時間: 2025-3-31 01:37
Inferring Deterministic Regular Expression with Unorder and Countingn this paper, schemata are inferred from unordered XML documents. We extend the single-occurrence regular expressions (SOREs) to single-occurrence regular expressions with unorder and counting (SOREUCs), and give an inference algorithm for SOREUCs. First, we present a . (FAUC). Then, we construct an作者: 禍害隱伏 時間: 2025-3-31 07:39 作者: COMA 時間: 2025-3-31 10:45 作者: 不透氣 時間: 2025-3-31 15:26 作者: Bone-Scan 時間: 2025-3-31 18:15 作者: 改正 時間: 2025-3-31 23:17 作者: Left-Atrium 時間: 2025-4-1 04:07 作者: Harness 時間: 2025-4-1 08:42
India and Iran Too Close for Comforted global feature information. Some approaches that split an entire text into multiple segments for feature extracting, which generates noise features of irrelevant segments. To address these issues, we introduce key-sentences extraction task with semi-supervised learning to quickly distinguish rele作者: 車床 時間: 2025-4-1 11:53
