Cover image for Advanced Data Mining and Applications 19th International Conference, ADMA 2023, Shenyang, China, August 21-23, 2023, Proceedings, Part III
Title:
Advanced Data Mining and Applications 19th International Conference, ADMA 2023, Shenyang, China, August 21-23, 2023, Proceedings, Part III
Author:
Yang, Xiaochun. editor.
ISBN:
9783031466717
Edition:
1st ed. 2023.
Physical Description:
XXI, 370 p. 136 illus., 86 illus. in color. online resource.
Series:
Lecture Notes in Artificial Intelligence, 14178
Contents:
Pharmaceutical Data Analysis -- Drug-target interaction prediction based on drug subgraph fingerprint extraction strategy and subgraph attention mechanism -- Soft Prompt Transfer for Zero-Shot and Few-Shot Learning in EHR Understanding -- Graph Convolution Synthetic Transformer for Chronic Kidney Disease Onset Prediction -- MTFL: Multi-task feature learning with joint correlation structure learning for Alzheimer's disease cognitive performance prediction -- Multi-Level Transformer for Cancer Outcome Prediction in Large-Scale Claims Data -- Individual Functional Network Abnormalities Mapping via Graph Representation-based Neural Architecture Search -- A novel application of a mutual information measure for analysing temporal changes in healthcare network graphs -- Drugs Resistance Analysis from Scarce Health Records via Multi-task Graph Representation -- Text Classification -- ParaNet:Parallel Networks with Pre-trained Models for Text Classification -- Open Text Classification Based on Dynamic Boundary Balance -- A Prompt Tuning Method for Chinese Medical Text Classification -- TabMentor: Detect Errors on Tabular Data with Noisy Labels -- Label-aware Hierarchical Contrastive Domain Adaptation for Cross-network Node Classification -- Semi-supervised classification based on Graph Convolution Encoder Representations from BERT -- Global Balanced Text Classification for Stable Disease Diagnosis -- Graph -- Dominance Maximization in Uncertain Graphs -- LAGCL: Towards Stable and Automated Graph Contrastive Learning -- Discriminative Graph-level Anomaly Detection via Dual-students-teacher Model -- Common-Truss-based Community Search on Multilayer Graphs -- Learning To Predict Shortest Path Distance -- Efficient Regular Path Query Evaluation with Structural Path Constraints.EnSpeciVAT: Enhanced SpeciVAT for Cluster Tendency Identification in Graphs -- Pessimistic Adversarially Regularized Learning for Graph Embedding -- M2HGCL: Multi-Scale Meta-Path Integrated Heterogeneous Graph Contrastive Learning.
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