Advances in knowledge discovery and data mining . Part I : 25th Pacific-Asia Conference, PAKDD 2021, Virtual Event, May 11-14, 2021, proceedings / / Kamal Karlapalem [and six others] (editors)

• Pubblicazione: Cham, Switzerland : , : Springer, , [2021]; ©2021
• Edizione: 1st ed. 2021.
• Descrizione fisica: 1 online resource (XXXV, 834 p. 30 illus.)
• Disciplina: 006.3
• Soggetto topico: Data mining
• Persona (resp. second.): KarlapalemKamal
• Nota di contenuto: 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.
• Sommario/riassunto: 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.
• Titolo autorizzato: Advances in Knowledge Discovery and Data Mining
• ISBN: 3-030-75762-5
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910484222603321
• Lo trovi qui: Univ. Federico II
• Serie: Lecture Notes in Artificial Intelligence ; ; 12712