89 Result(s)
within
English
Artificial Intelligence
Data Mining and Knowledge Discovery
Dong-**ng Wang
Conference Paper
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Chapter and Conference Paper
Adaptive Rounding Compensation for Post-training Quantization
Network quantization can compress and accelerate deep neural networks by reducing the bit-width of network parameters so that the quantized networks can be deployed to resource-limited devices. Post-Training Q...
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Chapter and Conference Paper
Training Noise Robust Deep Neural Networks with Self-supervised Learning
Training accurate deep neural networks (DNNs) on datasets with label noise is challenging for practical applications. The sample selection paradigm is a popular strategy that selects potentially clean data fro...
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Chapter and Conference Paper
Multi-modal Multi-emotion Emotional Support Conversation
This paper proposes a new task of Multi-modal Multi-emotion Emotional Support Conversation (MMESC), which has great value in various applications, such as counseling, daily chatting, and elderly company. This tas...
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Chapter and Conference Paper
User Interaction-Aware Knowledge Graphs for Recommender Systems
The performance of recommender systems can be improved effectively by using knowledge graphs as auxiliary information. However, most of the knowledge graph-based recommendations focus on learning item represen...
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Chapter and Conference Paper
GeoGTI: Towards a General, Transferable and Interpretable Site Recommendation
Lack of data and weak interpretability are the main problems faced by store site recommendations. This paper presents a unified site recommendation system called GeoGTI (General,Transferable and Interpretable), w...
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Chapter and Conference Paper
Efficient Dual-Process Cognitive Recommender Balancing Accuracy and Diversity
In this paper, we propose a dual-process cognitive recommendation system for sequential recommendations. The framework includes an intuitive representation module (System 1) and an inference module (System 2)....
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Chapter and Conference Paper
PhotoStylist: Altering the Style of Photos Based on the Connotations of Texts
The need to modify a photo to reflect the connotations of a text can arise due to multifarious reasons (e.g., a musician might modify a photo in the album cover to better reflect the connotations in her song l...
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Chapter and Conference Paper
AA-LSTM: An Adversarial Autoencoder Joint Model for Prediction of Equipment Remaining Useful Life
Remaining Useful Life (RUL) prediction of equipment can estimate the time when equipment reaches the safe operating limit, which is essential for strategy formulation to reduce the possibility of loss due to u...
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Chapter and Conference Paper
Generating Contextually Coherent Responses by Learning Structured Vectorized Semantics
Generating contextually coherent responses has been one of the most critical challenges in building intelligent dialogue systems. Key issues are how to appropriately encode contexts and how to make good use of...
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Chapter and Conference Paper
Link Prediction of Heterogeneous Information Networks Based on Frequent Subgraph Evolution
The problem of link prediction in heterogeneous information networks has been widely studied in recent years. It is essential to grasp the evolution law for both static information networks and dynamic informa...
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Chapter and Conference Paper
Consistency- and Inconsistency-Aware Multi-view Subspace Clustering
Multi-view subspace clustering has emerged as a crucial tool to solve the multi-view clustering problem. However, many of the existing methods merely focus on the consistency issue when learning the multi-view...
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Chapter and Conference Paper
GLAD-PAW: Graph-Based Log Anomaly Detection by Position Aware Weighted Graph Attention Network
Anomaly detection is a crucial and challenging subject that has been studied within diverse research areas. In this work, we focus on log data (especially computer system logs) which is a valuable source to in...
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Chapter and Conference Paper
Graph Attention Networks for New Product Sales Forecasting in E-Commerce
Aiming to discover competitive new products, sales forecasting has been playing an increasingly important role in real-world E-Commerce systems. Current methods either only utilize historical sales records wit...
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Chapter and Conference Paper
Deep Attributed Network Embedding Based on the PPMI
The attributed network embedding aims to learn the latent low-dimensional representations of nodes, while preserving the neighborhood relationship of nodes in the network topology as well as the similarities o...
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Chapter and Conference Paper
Joint Deep Recurrent Network Embedding and Edge Flow Estimation
The two most important tasks of network analysis are network embedding and edge flow estimation. The network embedding task seeks to represent each node as a continuous vector, and the edge flow estimation see...
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Chapter and Conference Paper
Proof of Activity Consensus Algorithm Based on Credit Reward Mechanism
Proof of Activity (PoA) is a key algorithm to reach consensus among nodes. In current PoA, N online representative nodes are only used to create one transaction block, and the probability of creating a block b...
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Chapter and Conference Paper
Automatic Detection of Solar Radio Spectrum Based on Codebook Model
Space weather can affect human production and life, and solar radio burst will seriously affect space weather. Automatic detection of solar radio bursts in real time has a positive effect on space weather warn...
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Chapter and Conference Paper
Online Programming Education Modeling and Knowledge Tracing
With the development of computer technology, more and more people begin to learn programming. And there are a lot of platforms for programmers to practice. It’s often difficult for these platforms to customize...
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Chapter and Conference Paper
State Evaluation of Electric Bus Battery Capacity Based on Big Data
Compared with traditional fuel vehicles, electric vehicles have the advantages of low carbon, low pollution and low noise. At present, major auto manufacturers are actively exploring the field of electric vehi...
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Chapter and Conference Paper
A New Method of Metaphor Recognition for A-is-B Model in Chinese Sentences
Metaphor recognition is the bottleneck of natural language processing, and the metaphor recognition for A-is-B mode is the difficulty of metaphor recognition. Compared with phrase recognition, the metaphor rec...
