派博傳思國際中心

標題: Titlebook: Database Systems for Advanced Applications; 25th International C Yunmook Nah,Bin Cui,Steven Euijong Whang Conference proceedings 2020 Sprin [打印本頁]

作者: Awkward    時間: 2025-3-21 18:58
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)學科排名




書目名稱Database Systems for Advanced Applications網絡公開度




書目名稱Database Systems for Advanced Applications網絡公開度學科排名




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讀者反饋學科排名





作者: OVER    時間: 2025-3-21 22:18

作者: cocoon    時間: 2025-3-22 01:58
Contemporary Issues in Marketingl reviews for rating prediction. Extensive experiments on four real-world datasets demonstrate that our model achieves the state-of-the-art performance in both rating prediction and review generation tasks.
作者: Sedative    時間: 2025-3-22 07:22
https://doi.org/10.1057/9781137025807quantify result error progressively. We implemented this method in our system called Parrot on top of Apache Spark and used real-world data to test its performance. Experiments demonstrate that our method is 2.4x–19.7x faster to get a result within 1% error while the confidence interval always covers the accurate results very well.
作者: geriatrician    時間: 2025-3-22 10:54

作者: Obsessed    時間: 2025-3-22 15:31
Adversarial Generation of Target Review for Rating Predictionl reviews for rating prediction. Extensive experiments on four real-world datasets demonstrate that our model achieves the state-of-the-art performance in both rating prediction and review generation tasks.
作者: Obsessed    時間: 2025-3-22 20:31

作者: 修飾語    時間: 2025-3-22 23:11
0302-9743 which will be held online in September 2020...The 119 full papers presented together with 19 short papers plus 15 demo papers and 4 industrial papers in this volume were carefully reviewed and selected from a total of 487 submissions...The conference program presents the state-of-the-art R&D activi
作者: ADORN    時間: 2025-3-23 02:21

作者: PATRI    時間: 2025-3-23 06:20
Conference proceedings 2020olume were carefully reviewed and selected from a total of 487 submissions...The conference program presents the state-of-the-art R&D activities in database systems and their applications. It provides a forum for technical presentations and discussions among database researchers, developers and users from academia, business and industry..
作者: 比目魚    時間: 2025-3-23 10:23

作者: chastise    時間: 2025-3-23 17:53
Contemporary Issues in Macroeconomicsng records. MRMRP is capable of extracting useful features from supplementary reviews to further improve recommendation performance by applying a deep learning based method. Moreover, the supplementary reviews can be incorporated into different neural models to boost rating prediction accuracy. Expe
作者: 漂白    時間: 2025-3-23 18:15
https://doi.org/10.1007/978-1-349-14299-6egmentation) have different labels from the bag’s (segmentation’s) label. The prototype is the center of the instances in WPN rather than less discriminative bags, which determines the bag-level classification accuracy. To get the most representative instance-level prototype, we propose two strategi
作者: Interdict    時間: 2025-3-23 23:58
Martin Guzman,Joseph E. Stiglitza sentence, we adopt a self-attention component to generate sentence level representations and then measure their relevance with a neural tensor network. To better utilize the interaction information, we devise an inter-attention component to further consider the influence of one sentence on another
作者: 減至最低    時間: 2025-3-24 06:24
Contemporary Issues in Microeconomicsd show that the interpretation issues can be addressed by including a family of utility functions in the space of instance embedding. Following this route, we propose a novel Permutation-Invariant Operator to improve the instance-level interpretability of MIL as well as the overall performance. We a
作者: maverick    時間: 2025-3-24 07:27
The Role of Mining in the Australian Economybles of input data by minimizing the combination of latent error and neural density. The neural density of input data can be estimated naturally by ADAF, along with the latent variable inference, rather than through an additional stitched density estimation network. Unlike stitching decoupled models
作者: 不舒服    時間: 2025-3-24 12:53
https://doi.org/10.1057/9781137025807on this KG embedding model, we perform entity typing from coarse-grained level to more fine-grained level hierarchically. Besides, we also propose ways to utilize zero-shot attribute values that never appear in the training set. Our experiments performed on real-world KGs show that our approach is s
作者: fender    時間: 2025-3-24 17:18
Practical Problems in Mining Valuationsncoder that can handle any set of feature values in various sizes. And the selector efficiently learns the cost-effective strategy based on the state-of-art reinforcement learning techniques. Experimental results have shown that under the same classification accuracy, our strategy is superior to oth
作者: meretricious    時間: 2025-3-24 21:14

作者: 哀求    時間: 2025-3-24 23:22

作者: 為現(xiàn)場    時間: 2025-3-25 04:30

作者: Perineum    時間: 2025-3-25 08:14

作者: Thyroxine    時間: 2025-3-25 15:31
https://doi.org/10.1007/978-3-031-45222-2s, we leverage a LSTM-based structure to learn intrinsic temporal dependencies so as to capture the evolution of activity sequences. For in-game behaviors, we develop a time-aware filtering component to better distinguish the behavior patterns occurring in a specific period and a multi-view mechanis
作者: 遷移    時間: 2025-3-25 17:54

作者: panorama    時間: 2025-3-25 22:10
Massimo Arnone,Tiziana Crovellavel variant of LSTM and a novel attention mechanism. The proposed LSTM is able to learn student profile-aware representation from the heterogeneous behavior sequences. The proposed attention mechanism can dynamically learn the different importance degrees of different days for every student. With mu
作者: 同步左右    時間: 2025-3-26 00:47
EPARS: Early Prediction of At-Risk Students with Online and Offline Learning Behaviorsrse data. Second, friends of STAR are more likely to be at risk. We constructed a co-occurrence network to approximate the underlying social network and encode the social homophily as features through network embedding. To validate the proposed algorithm, extensive experiments have been conducted am
作者: Cryptic    時間: 2025-3-26 04:29
MRMRP: Multi-source Review-Based Model for Rating Predictionng records. MRMRP is capable of extracting useful features from supplementary reviews to further improve recommendation performance by applying a deep learning based method. Moreover, the supplementary reviews can be incorporated into different neural models to boost rating prediction accuracy. Expe
作者: custody    時間: 2025-3-26 09:21
Few-Shot Human Activity Recognition on?Noisy Wearable Sensor Dataegmentation) have different labels from the bag’s (segmentation’s) label. The prototype is the center of the instances in WPN rather than less discriminative bags, which determines the bag-level classification accuracy. To get the most representative instance-level prototype, we propose two strategi
作者: ALLAY    時間: 2025-3-26 13:01

作者: 歹徒    時間: 2025-3-26 17:06
Instance Explainable Multi-instance Learning for ROI of Various Datad show that the interpretation issues can be addressed by including a family of utility functions in the space of instance embedding. Following this route, we propose a novel Permutation-Invariant Operator to improve the instance-level interpretability of MIL as well as the overall performance. We a
作者: 撤退    時間: 2025-3-27 00:19

作者: Adenocarcinoma    時間: 2025-3-27 03:33

作者: Indict    時間: 2025-3-27 05:21

作者: declamation    時間: 2025-3-27 12:36
Bus Frequency Optimization: When Waiting Time Matters in User Satisfactiontition-based greedy method which achieves a . approximation ratio. Then we propose a progressive partition-based greedy method to further improve the efficiency while achieving a . approximation ratio. Experiments on a real city-wide bus dataset in Singapore verify the efficiency, effectiveness, and
作者: incite    時間: 2025-3-27 15:05
Incorporating Boundary and Category Feature for Nested Named Entity Recognitionon. In this way, our model achieves better performance of entity extraction. In evaluations on two nested NER datasets and a flat NER dataset, we show that our model outperforms previous state-of-the-art models on nested and flat NER.
作者: ALTER    時間: 2025-3-27 20:23
Incorporating Concept Information into Term Weighting Schemes for Topic Modelsument. The DCEP scheme further reduces the co-occurrence of the entities from unrelated concepts and separates them into different duplicates of a document. We develop CEP-LDA and DCEP-LDA term weighting topic models by applying the two proposed term weighting schemes to LDA. Experimental results on
作者: liposuction    時間: 2025-3-28 00:47
How to Generate Reasonable Texts with Controlled Attributeso guide each component of our model to collaboratively work for generating reasonable texts based on the learned dependencies, and (3) proposing a novel . metric measuring to which degree generations comply with real co-occurrence dependencies. Experiments prove that DCTG outperforms state-of-the-ar
作者: conceal    時間: 2025-3-28 05:39

作者: Diuretic    時間: 2025-3-28 10:17

作者: 極小    時間: 2025-3-28 10:30

作者: foreign    時間: 2025-3-28 16:45
EPARS: Early Prediction of At-Risk Students with Online and Offline Learning Behaviorsks mostly rely on either online or offline learning behaviors which are not comprehensive enough to capture the whole learning processes and lead to unsatisfying prediction performance. We propose a novel algorithm (EPARS) that could early predict STAR in a semester by modeling online and offline le
作者: 傳授知識    時間: 2025-3-28 21:25
MRMRP: Multi-source Review-Based Model for Rating Predictionfew years, many studies in recommender systems take user reviews into consideration and achieve promising performance. However, in daily life, most consumers are used to leaving no comments for products purchased and most reviews written by consumers are short, which leads to the performance degrada
作者: CORD    時間: 2025-3-28 23:52

作者: Debark    時間: 2025-3-29 06:06
Few-Shot Human Activity Recognition on?Noisy Wearable Sensor Datanew-class activities unseen during training from a few samples. Very few researches of few-shot learning (FSL) have been done in HAR to address the above problem, though FSL has been widely used in computer vision tasks. Besides, it is impractical to annotate sensor data with accurate activity label
作者: 綠州    時間: 2025-3-29 09:00
Adversarial Generation of Target Review for Rating Predictionisting methods learn the latent representations from the user’s and the item’s historical reviews, and then combine these two representations for rating prediction. The fatal limitation in these methods is that they are unable to utilize the most predictive review of the target user for the target i
作者: 微粒    時間: 2025-3-29 14:43
Hybrid Attention Based Neural Architecture for Text Semantics Similarity Measurementguage processing. It is a complicated task due to the ambiguity and variability of linguistic expression. Previous studies focus on modeling the representation of a sentence in multiple granularities and then measure the similarity based on the representations. However, above methods cannot make ful
作者: 卡死偷電    時間: 2025-3-29 16:12
Instance Explainable Multi-instance Learning for ROI of Various Dataion can be generalized to the bag containing multiple data instances, i.e., identify the instances that probably arouse our interest. Under the circumstance without instance labels, generalized ROI estimation problem can be addressed in the framework of Multi-Instance Learning (MIL). MIL is a variat
作者: BRAWL    時間: 2025-3-29 23:14

作者: 無王時期,    時間: 2025-3-30 00:26

作者: pulmonary-edema    時間: 2025-3-30 06:56
Progressive Term Frequency Analysis on?Large Text Collectionsep up with the growth of data. The delays when processing huge textual data can negatively impact user activity and insight. This calls for a paradigm shift from blocking fashion to progressive processing. In this paper, we propose a sample-based progressive processing model that focuses on term fre
作者: stressors    時間: 2025-3-30 09:03
Learning a Cost-Effective Strategy on Incomplete Medical Dataessible, which is unrealistic since most features come at a cost. Under a medical scenario, each feature is associated with a medical test that costs a certain amount of money. And doctors would ask patients to do consecutive tests until they are confident enough to make a final diagnosis, whereas t
作者: compose    時間: 2025-3-30 12:43

作者: 勾引    時間: 2025-3-30 18:14
Incorporating Boundary and Category Feature for Nested Named Entity Recognition (NER) models focus on flat entities but ignore nested entities. In this paper, we propose a neural model for nested named entity recognition. Our model employs a multi-label boundary detection module to detect entity boundaries, avoiding boundary detection conflict existing in the boundary-aware mo
作者: Neutropenia    時間: 2025-3-30 23:14

作者: 斗志    時間: 2025-3-31 01:46

作者: HAVOC    時間: 2025-3-31 05:23

作者: 合乎習俗    時間: 2025-3-31 09:39

作者: STALL    時間: 2025-3-31 15:03
Learning from Heterogeneous Student Behaviors for Multiple Prediction Taskst will fail to graduate can alert the university student affairs office to take predictive measures to help the student improve academic performance. In this paper, we focus on making multiple predictions together, since leaning the model for a specific task may have the data-sparsity problem. With
作者: 袖章    時間: 2025-3-31 19:37

作者: aviator    時間: 2025-4-1 00:21
978-3-030-59415-2Springer Nature Switzerland AG 2020
作者: Flat-Feet    時間: 2025-4-1 02:19

作者: patriot    時間: 2025-4-1 08:57

作者: Triglyceride    時間: 2025-4-1 13:40

作者: flamboyant    時間: 2025-4-1 18:19
https://doi.org/10.1007/978-1-349-14299-6iven location changes with different environments. Existing methods fail to capture real-time traffic conditions instantly. This paper provides the first attempt to discover real-time reachable areas with real-time trajectories. To address the data sparsity issue raised by the limited real-time traj




歡迎光臨 派博傳思國際中心 (http://www.pjsxioz.cn/) Powered by Discuz! X3.5
连云港市| 石台县| 五家渠市| 新沂市| 昆山市| 博客| 枣阳市| 东兴市| 吐鲁番市| 周口市| 长乐市| 仪陇县| 永靖县| 田阳县| 绵阳市| 广饶县| 哈巴河县| 吴忠市| 延川县| 日喀则市| 洞头县| 塔河县| 同心县| 开封县| 潮安县| 灵丘县| 虞城县| 巧家县| 嘉荫县| 云和县| 淳安县| 邵阳市| 饶阳县| 龙山县| 秦安县| 马山县| 宝丰县| 汝南县| 工布江达县| 通化市| 闽侯县|