Del i serien Lecture Notes in Computer Science

Advanced Data Mining and Applications

19th International Conference, ADMA 2023, Shenyang, China, August 21–23, 2023, Proceedings, Part III

Häftad, Engelska, 2023

AvXiaochun Yang,Heru Suhartanto,Guoren Wang,Bin Wang,Jing Jiang,Bing Li,Huaijie Zhu,Ningning Cui

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They were organized in topical sections as follows: Data mining foundations, Grand challenges of data mining, Parallel and distributed data mining algorithms, Mining on data streams, Graph mining and Spatial data mining.

Produktinformation

Utgivningsdatum2023-11-05
Mått155 x 235 x 22 mm
Vikt593 g
FormatHäftad
SpråkEngelska
SerieLecture Notes in Computer Science
Antal sidor370
FörlagSpringer International Publishing AG
ISBN9783031466700

Tillhör följande kategorier

Tillämpad datateknik inom Data och IT
Systemvetenskap och AI inom Data och IT
Artificiell intelligens inom Data och IT
Databaser inom Data och IT

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.