123 Result(s)
within
Ying**g Zhang
Computer Science
Data Mining and Knowledge Discovery
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Article
Multi-representation web service recommendation system based on attention mechanism
Recently, mashup developers seek to integrate multiple services with complementary functionalities from a large amount of web services. With so many available web services, it is difficult for developers to ch...
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Article
Open AccessShort-term multi-step-ahead sector-based traffic flow prediction based on the attention-enhanced graph convolutional LSTM network (AGC-LSTM)
Accurate sector-based air traffic flow predictions are essential for ensuring the safety and efficiency of the air traffic management (ATM) system. However, due to the inherent spatial and temporal dependencie...
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Article
Open AccessMAFSIDS: a reinforcement learning-based intrusion detection model for multi-agent feature selection networks
Large unbalanced datasets pose challenges for machine learning models, as redundant and irrelevant features can hinder their effectiveness. Furthermore, the performance of intrusion detection systems (IDS) can...
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Article
Open AccessSCRE: special cargo relation extraction using representation learning
The airfreight industry of ship** goods with special handling needs, also known as special cargo, often deals with non-transparent data and outdated technology, resulting in significant inefficiency. A speci...
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Article
CoConGAN: Cooperative contrastive learning for few-shot cross-domain heterogeneous face translation
The inherently uneven informative setting in heterogeneous face images makes heterogeneous face translation challenging for synthesizing the analogous face image which preserves the identity of the input image...
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Article
Open AccessRisk and UCON-based access control model for healthcare big data
The rapid development of healthcare big data has brought certain convenience to medical research and health management, but privacy protection of healthcare big data is an issue that must be considered in the ...
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Article
An algorithm of nonnegative matrix factorization under structure constraints for image clustering
Nonnegative matrix factorization (NMF) is a crucial method for image clustering. However, NMF may obtain low accurate clustering results because the factorization results contain no data structure information....
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Article
EDense: a convolutional neural network with ELM-based dense connections
The explosive growth of geospatial data is increasing requirements for automatic and efficient data learning abilities. Many deep learning methods have been widely applied for geospatial data understanding tas...
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Chapter and Conference Paper
Evaluation of Deep Reinforcement Learning Based Stock Trading
Stock is one of the most important targets in investment. However, it is challenging to manually design a profitable strategy in the highly dynamic and complex stock market. Modern portfolio management usually...
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Chapter
Sequential Pattern Mining in Educational Data: The Application Context, Potential, Strengths, and Limitations
Increasingly, researchers have suggested the benefits of temporal analyses to improve our understanding of the learning process. Sequential pattern mining (SPM), as a pattern recognition technique, has the pot...
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Chapter and Conference Paper
DHA: Product Title Generation with Discriminative Hierarchical Attention for E-commerce
Product titles play an important role in E-Commerce sites. However, manually crafting product titles needs tremendous time and human effort. It is expected that product titles can be automatically generated, b...
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Chapter and Conference Paper
Dynamic Alternative Attention for Visual Question Answering
In recent years, researchers have focused on Visual Question Answering (VQA) due to its numerous real-world applications. And visual attention mechanisms are widely used to assist answer prediction by selectin...
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Chapter and Conference Paper
DEAR: Dual-Level Self-attention GRU for Online Early Prediction of Sepsis
Sepsis is one of the leading causes of death in intensive care units (ICUs). Online early prediction of sepsis has the potential for application to support clinicians. Despite the great success of deep neural ...
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Chapter
Knowledge Modeling and Incident Analysis for Special Cargo
The airfreight industry of ship** goods with special handling needs, also known as special cargo, suffers from nontransparent ship** processes, resulting in inefficiency. The LARA project (Lane Analysis an...
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Article
Discovering fortress-like cohesive subgraphs
Morris (Rev Econ Stud 67:57–78, 2000) defines the \(p\) p -cohesion by a con...
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Article
Transfer of semi-supervised broad learning system in electroencephalography signal classification
Electroencephalography (EEG) signal classification is a crucial part in motor imagery brain–computer interface (BCI) system. Traditional supervised learning methods have performed well pleasing in EEG classifi...
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Chapter and Conference Paper
A Decision Support System for Heart Failure Risk Prediction Based on Weighted Naive Bayes
Heart failure (HF) affects the health of millions of people worldwide and the early detection of HF risk plays a vital role in prevention and prompt treatment. Various decision support systems based on machine...
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Chapter and Conference Paper
STMG: Spatial-Temporal Mobility Graph for Location Prediction
Location-Based Social Networks (LBSNs) data reflects a large amount of user mobility patterns. So it is possible to infer users’ unvisited Points of Interest (POIs) through the users’ check-in records in LBSNs...
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Chapter and Conference Paper
ImputeRNN: Imputing Missing Values in Electronic Medical Records
Electronic Medical Records (EMRs), which record visits of patients to the hospital, are the main resources for medical data analysis. However, plenty of missing values in EMRs limit the model capability for va...
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Chapter and Conference Paper
Prognosis Prediction of Breast Cancer Based on CGAN
Breast cancer is the malignancy with the highest morbidity and mortality rate in women worldwide, and prognosis prediction of breast cancer is of great practical importance for both patients and clinical pract...
