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- research-articleJune 2024
Congestion-aware Spatio-Temporal Graph Convolutional Network-based A* Search Algorithm for Fastest Route Search
ACM Transactions on Knowledge Discovery from Data (TKDD), Volume 18, Issue 7Article No.: 179, Pages 1–19https://doi.org/10.1145/3657640The fastest route search, which is to find a path with the shortest travel time when the user initiates a query, has become one of the most important services in many map applications. To enhance the user experience of travel, it is necessary to achieve ...
- research-articleJune 2024
Computing Random Forest-distances in the presence of missing data
ACM Transactions on Knowledge Discovery from Data (TKDD), Volume 18, Issue 7Article No.: 180, Pages 1–18https://doi.org/10.1145/3656345In this article, we study the problem of computing Random Forest-distances in the presence of missing data. We present a general framework which avoids pre-imputation and uses in an agnostic way the information contained in the input points. We centre our ...
- research-articleJune 2024
Toward Few-Label Vertical Federated Learning
ACM Transactions on Knowledge Discovery from Data (TKDD), Volume 18, Issue 7Article No.: 176, Pages 1–21https://doi.org/10.1145/3656344Federated Learning (FL) provides a novel paradigm for privacy-preserving machine learning, enabling multiple clients to collaborate on model training without sharing private data. To handle multi-source heterogeneous data, Vertical Federated Learning (VFL)...
- research-articleJune 2024
TOMGPT: Reliable Text-Only Training Approach for Cost-Effective Multi-modal Large Language Model
ACM Transactions on Knowledge Discovery from Data (TKDD), Volume 18, Issue 7Article No.: 171, Pages 1–19https://doi.org/10.1145/3654674Multi-modal large language models (MLLMs), such as GPT-4, exhibit great comprehension capabilities on human instruction, as well as zero-shot ability on new downstream multi-modal tasks. To integrate the different modalities within a unified embedding ...
- research-articleJune 2024
Towards Robust Rumor Detection with Graph Contrastive and Curriculum Learning
ACM Transactions on Knowledge Discovery from Data (TKDD), Volume 18, Issue 7Article No.: 175, Pages 1–21https://doi.org/10.1145/3653023Establishing a robust rumor detection model is vital in safeguarding the veracity of information on social media platforms. However, existing approaches to stopping rumor from spreading rely on abundant and clean training data, which is rarely available ...
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- research-articleJune 2024
Dual-Side Adversarial Learning Based Fair Recommendation for Sensitive Attribute Filtering
ACM Transactions on Knowledge Discovery from Data (TKDD), Volume 18, Issue 7Article No.: 165, Pages 1–20https://doi.org/10.1145/3648683With the development of recommendation algorithms, researchers are paying increasing attention to fairness issues such as user discrimination in recommendations. To address these issues, existing works often filter users’ sensitive information that may ...
- research-articleJune 2024
Voxel-Wise Medical Image Generalization for Eliminating Distribution Shift
ACM Transactions on Knowledge Discovery from Data (TKDD), Volume 18, Issue 7Article No.: 167, Pages 1–16https://doi.org/10.1145/3643034Currently, the medical field is witnessing an increase in the use of machine learning techniques. Supervised learning methods adopted in classification, prediction, and segmentation tasks for medical images always experience decreased performance when the ...
- research-articleMay 2024JUST ACCEPTED
Mobile User Traffic Generation via Multi-Scale Hierarchical GAN
ACM Transactions on Knowledge Discovery from Data (TKDD), Just Accepted https://doi.org/10.1145/3664655Mobile user traffic facilitates diverse applications, including network planning and optimization, whereas large-scale mobile user traffic is hardly available due to privacy concerns. One alternative solution is to generate mobile user traffic data for ...
- research-articleMay 2024JUST ACCEPTED
FastHGNN: A New Sampling Technique for Learning with Hypergraph Neural Networks
ACM Transactions on Knowledge Discovery from Data (TKDD), Just Accepted https://doi.org/10.1145/3663670Hypergraphs can represent higher-order relations among objects. Traditional hypergraph neural networks involve node-edge-node transform, leading to high computational cost and timing. The main aim of this paper is to propose a new sampling technique for ...
- research-articleMay 2024JUST ACCEPTED
Variate Associated Domain Adaptation for Unsupervised Multivariate Time Series Anomaly Detection
ACM Transactions on Knowledge Discovery from Data (TKDD), Just Accepted https://doi.org/10.1145/3663573Multivariate Time Series Anomaly Detection (MTS-AD) is crucial for the effective management and maintenance of devices in complex systems such as server clusters, spacecrafts and financial systems etc. However, upgrade or cross-platform deployment of ...
- research-articleMay 2024JUST ACCEPTED
EML: Emotion-Aware Meta Learning for Cross-Event False Information Detection
ACM Transactions on Knowledge Discovery from Data (TKDD), Just Accepted https://doi.org/10.1145/3661485Modern social media’s development has dramatically changed how people obtain information. However, the wide dissemination of various false information has severely detrimental effects. Accordingly, many deep learning-based methods have been proposed to ...
- research-articleApril 2024
NOODLE: Joint Cross-View Discrepancy Discovery and High-Order Correlation Detection for Multi-View Subspace Clustering
ACM Transactions on Knowledge Discovery from Data (TKDD), Volume 18, Issue 6Article No.: 151, Pages 1–23https://doi.org/10.1145/3653305Benefiting from the effective exploration of the valuable topological pair-wise relationship of data points across multiple views, multi-view subspace clustering (MVSC) has received increasing attention in recent years. However, we observe that existing ...
- research-articleApril 2024
DeepMeshCity: A Deep Learning Model for Urban Grid Prediction
ACM Transactions on Knowledge Discovery from Data (TKDD), Volume 18, Issue 6Article No.: 148, Pages 1–26https://doi.org/10.1145/3652859Urban grid prediction can be applied to many classic spatial-temporal prediction tasks such as air quality prediction, crowd density prediction, and traffic flow prediction, which is of great importance to smart city building. In light of its practical ...
- research-articleApril 2024
MoMENt: Marked Point Processes with Memory-Enhanced Neural Networks for User Activity Modeling
ACM Transactions on Knowledge Discovery from Data (TKDD), Volume 18, Issue 6Article No.: 155, Pages 1–32https://doi.org/10.1145/3649504Marked temporal point process models (MTPPs) aim to model event sequences and event markers (associated features) in continuous time. These models have been applied to various application domains where capturing event dynamics in continuous time is ...
- research-articleApril 2024
Representative and Back-In-Time Sampling from Real-world Hypergraphs
ACM Transactions on Knowledge Discovery from Data (TKDD), Volume 18, Issue 6Article No.: 156, Pages 1–48https://doi.org/10.1145/3653306Graphs are widely used for representing pairwise interactions in complex systems. Since such real-world graphs are large and often evergrowing, sampling subgraphs is useful for various purposes, including simulation, visualization, stream processing, ...
- research-articleApril 2024
Node Embedding Preserving Graph Summarization
ACM Transactions on Knowledge Discovery from Data (TKDD), Volume 18, Issue 6Article No.: 145, Pages 1–19https://doi.org/10.1145/3649505Graph summarization is a useful tool for analyzing large-scale graphs. Some works tried to preserve original node embeddings encoding rich structural information of nodes on the summary graph. However, their algorithms are designed heuristically and not ...
- research-articleApril 2024
DP-GCN: Node Classification by Connectivity and Local Topology Structure on Real-World Network
ACM Transactions on Knowledge Discovery from Data (TKDD), Volume 18, Issue 6Article No.: 140, Pages 1–20https://doi.org/10.1145/3649460Node classification is to predict the class label of a node by analyzing its properties and interactions in a network. We note that many existing solutions for graph-based node classification only consider node connectivity but not the node’s local ...
- research-articleApril 2024
ProtoMGAE: Prototype-Aware Masked Graph Auto-Encoder for Graph Representation Learning
ACM Transactions on Knowledge Discovery from Data (TKDD), Volume 18, Issue 6Article No.: 137, Pages 1–22https://doi.org/10.1145/3649143Graph self-supervised representation learning has gained considerable attention and demonstrated remarkable efficacy in extracting meaningful representations from graphs, particularly in the absence of labeled data. Two representative methods in this ...
- research-articleApril 2024
Fairness-Aware Graph Neural Networks: A Survey
- April Chen,
- Ryan A. Rossi,
- Namyong Park,
- Puja Trivedi,
- Yu Wang,
- Tong Yu,
- Sungchul Kim,
- Franck Dernoncourt,
- Nesreen K. Ahmed
ACM Transactions on Knowledge Discovery from Data (TKDD), Volume 18, Issue 6Article No.: 138, Pages 1–23https://doi.org/10.1145/3649142Graph Neural Networks (GNNs) have become increasingly important due to their representational power and state-of-the-art predictive performance on many fundamental learning tasks. Despite this success, GNNs suffer from fairness issues that arise as a ...
- research-articleApril 2024
On Breaking Truss-based and Core-based Communities
ACM Transactions on Knowledge Discovery from Data (TKDD), Volume 18, Issue 6Article No.: 135, Pages 1–43https://doi.org/10.1145/3644077We introduce the general problem of identifying a smallest edge subset of a given graph whose deletion makes the graph community-free. We consider this problem under two community notions that have attracted significant attention: k-truss and k-core. We ...