Advances in Knowledge Discovery and Data Mining : 25th Pacific-Asia Conference, PAKDD 2021, Virtual Event, May 11-14, 2021, Proceedings, Part I / edited by Kamal Karlapalem, Hong Cheng, Naren Ramakrishnan, R. K. Agrawal, P. Krishna Reddy, Jaideep Srivastava, Tanmoy Chakraborty.

Format:

Book

Contributor:

Karlapalem, Kamal., Editor.

Cheng, Hong., Editor.

Ramakrishnan, Naren, Editor.

Agrawal, R. K., Editor.

Reddy, P. Krishna., Editor.

Srivastava, Jaideep, Editor.

Chakraborty, Tanmoy, Editor.

SpringerLink (Online service)

Series:

Computer Science (SpringerNature-11645)

Lecture notes in computer science. Lecture notes in artificial intelligence ; 12712

Lecture Notes in Artificial Intelligence ; 12712

Language:

English

Subjects (All):

Artificial intelligence.

Data mining.

Social sciences-Data processing.

Computer networks.

Algorithms.

Artificial Intelligence.

Data Mining and Knowledge Discovery.

Computer Application in Social and Behavioral Sciences.

Computer Communication Networks.

Design and Analysis of Algorithms.

Local Subjects:

Artificial Intelligence.

Data Mining and Knowledge Discovery.

Computer Application in Social and Behavioral Sciences.

Computer Communication Networks.

Design and Analysis of Algorithms.

Physical Description:

1 online resource (XXXV, 834 pages) : 30 illustrations

Edition:

1st ed. 2021.

Contained In:

Springer Nature eBook

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2021.

System Details:

text file PDF

Summary:

The 3-volume set LNAI 12712-12714 constitutes the proceedings of the 25th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2021, which was held during May 11-14, 2021. The 157 papers included in the proceedings were carefully reviewed and selected from a total of 628 submissions. They were organized in topical sections as follows: Part I: Applications of knowledge discovery and data mining of specialized data; Part II: Classical data mining; data mining theory and principles; recommender systems; and text analytics; Part III: Representation learning and embedding, and learning from data.

Contents:

Applications of Knowledge Discovery

Fuzzy World:A Tool Training Agent from Concept Cognitive to Logic Inference

Collaborative Reinforcement Learning Framework to Model Evolution of Cooperation in Sequential Social Dilemmas

SIGTRAN: Signature Vectors for Detecting Illicit Activities in Blockchain Transaction Networks

VOA*: Fast Angle-Based Outlier Detection Over High-Dimensional Data Streams

Learning Probabilistic Latent Structure for Outlier Detection from Multi-View Data

GLAD-PAW: Graph-based Log Anomaly Detection by Position Aware Weighted Graph Attention Network

CubeFlow: Money Laundering Detection with Coupled Tensors

Unsupervised Boosting-based Autoencoder Ensembles for Outlier Detection

Unsupervised Domain Adaptation for 3D Medical Image with High Efficiency

A Hierarchical Structure-Aware Embedding Method for Predicting Phenotype-Gene Associations

Autonomous Vehicle Path Prediction using Conditional Variational Autoencoder Networks

Heterogeneous Graph Attention Network for Small and Medium-sized Enterprises Bankruptcy Prediction

Algorithm Selection as Superset Learning: Constructing Algorithm Selectors from Imprecise Performance Data

Sim2Real for Metagenomes: Accelerating Animal Diagnostics with Adversarial Co-Training

Attack Is the Best Defense: A Multi-Mode Poisoning PUF against Machine Learning Attacks

Combining exogenous and endogenous signals with a semi-supervised co-attention network for early detection of COVID-19 fake tweets

TLife-LSTM: Forecasting Future COVID-19 Progression with Topological Signatures of Atmospheric Conditions

Lifelong Learning based Disease Diagnosis on Clinical Notes

GrabQC: Graph based Query Contextualization for automated ICD coding

Deep Gaussian Mixture Model on Multiple Interpretable Features of Fetal Heart Rate for Pregnancy Wellness

Adverse Drug Events Detection, Extraction and Normalization from Online Comments of Chinese Patent Medicines

Adaptive Graph Co-Attention Networks for Traffic Forecasting

Dual-Stage Bayesian Sequence to Sequence Embeddings for Energy Demand Forecasting

AA-LSTM: An Adversarial Autoencoder Joint Model for Prediction of Equipment Remaining Useful Life

Data Mining of Specialized Data

Analyzing Topic Transitions in Text-based Social Cascades using Dual-Network Hawkes Process

HiPaR: Hierarchical Pattern-Aided Regression

Improved Topology Extraction using Discriminative Parameter Mining of Logs

Back to Prior Knowledge: Joint Event Causality Extraction via Convolutional Semantic Infusion

A k-MCST based Algorithm for Discovering Core-Periphery Structures in Graphs

Detecting Sequentially Novel Classes with Stable Generalization Ability

Learning-based Dynamic Graph Stream Sketch

Discovering Dense Correlated Subgraphs in Dynamic Networks

Fake News Detection with Heterogenous Deep Graph Convolutional Network

Incrementally Finding the Vertices Absent from the Maximum Independent Sets

Neighbours and Kinsmen: Hateful Users Detection with Graph Neural Network

Graph Neural Networks for Soft Semi-Supervised Learning on Hypergraphs

A Meta-path based Graph Convolutional Network with Multi-Scale Semantic Extractions for Heterogeneous Event Classification

Noise-Enhanced Unsupervised Link Prediction

Weak Supervision Network Embedding for Constrained Graph Learning

RAGA: Relation-aware Graph Attention Networks for Global Entity Alignment

Graph Attention Networks with Positional Embeddings

Unified Robust Training for Graph Neural Networks against Label Noise

Graph InfoClust: Maximizing Coarse-Grain Mutual Information in Graphs

A Deep Hybrid Pooling Architecture for Graph Classification with Hierarchical Attention

Maximizing Explainability with SF-Lasso and Selective Inference for Video and Picture Ads. -Reliably Calibrated Isotonic Regression

Multiple Instance Learning for Unilateral Data

An Online Learning Algorithm for Non-Stationary Imbalanced Data by Extra-Charging Minority Class

Locally Linear Support Vector Machines for Imbalanced Data Classification. - Low-Dimensional Representation Learning from Imbalanced Data Streams

PhotoStylist: Altering the Style of Photos based on the Connotations of Texts

Gazetteer-Guided Keyphrase Generation from Research Papers

Minits-AllOcc: An Efficient Algorithm for Mining Timed Sequential Patterns

T^3N: Harnessing Text and Temporal Tree Network for Rumor Detection on Twitter

AngryBERT: Joint Learning Target and Emotion for Hate Speech Detection

SCARLET: Explainable Attention based Graph Neural Network for Fake News spreader prediction

Content matters: A GNN-based Model Combined with Text Semantics for Social Network Cascade Prediction

TERMCast: Temporal Relation Modeling for Effective Urban Flow Forecasting

Traffic Flow Driven Spatio-Temporal Graph Convolutional Network for Ride-hailing Demand Forecasting

A Proximity Forest for Multivariate Time Series Classification

C²-Guard: A Cross-Correlation Gaining Framework for Urban Air Quality Prediction

Simultaneous multiple POI population patternanalysis system with HDP mixture regression

Interpretable Feature Construction for Time Series Extrinsic Regression

SEPC: Improving Joint Extraction of Entities and Relations by Strengthening Entity Pairs Connection.

Other Format:

Printed edition:

ISBN:

978-3-030-75762-5

9783030757625

Access Restriction:

Restricted for use by site license.