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書名・著者名等
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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
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資料種別
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リモートファイル
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版
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1st ed. 2021
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出版者・出版年
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Cham : Springer International Publishing : Imprint: Springer , 2021
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形状・大きさ
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XXXV, 834 p. 30 illus : online resource
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巻号情報
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シリーズ名等
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Lecture Notes in Artificial Intelligence <> 12712//a
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内容著作注記
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Applications of Knowledge Discovery
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内容著作注記
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Fuzzy World:A Tool Training Agent from Concept Cognitive to Logic Inference
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Collaborative Reinforcement Learning Framework to Model Evolution of Cooperation in Sequential Social Dilemmas
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内容著作注記
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SIGTRAN: Signature Vectors for Detecting Illicit Activities in Blockchain Transaction Networks
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内容著作注記
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VOA*: Fast Angle-Based Outlier Detection Over High-Dimensional Data Streams
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内容著作注記
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Learning Probabilistic Latent Structure for Outlier Detection from Multi-View Data
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内容著作注記
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GLAD-PAW: Graph-based Log Anomaly Detection by Position Aware Weighted Graph Attention Network
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内容著作注記
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CubeFlow: Money Laundering Detection with Coupled Tensors
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Unsupervised Boosting-based Autoencoder Ensembles for Outlier Detection
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Unsupervised Domain Adaptation for 3D Medical Image with High Efficiency
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A Hierarchical Structure-Aware Embedding Method for Predicting Phenotype-Gene Associations
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Autonomous Vehicle Path Prediction using Conditional Variational Autoencoder Networks
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Heterogeneous Graph Attention Network for Small and Medium-sized Enterprises Bankruptcy Prediction
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Algorithm Selection as Superset Learning: Constructing Algorithm Selectors from Imprecise Performance Data
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内容著作注記
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Sim2Real for Metagenomes: Accelerating Animal Diagnostics with Adversarial Co-Training
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内容著作注記
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Attack Is the Best Defense: A Multi-Mode Poisoning PUF against Machine Learning Attacks
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内容著作注記
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Combining exogenous and endogenous signals with a semi-supervised co-attention network for early detection of COVID-19 fake tweets
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TLife-LSTM: Forecasting Future COVID-19 Progression with Topological Signatures of Atmospheric Conditions
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Lifelong Learning based Disease Diagnosis on Clinical Notes
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GrabQC: Graph based Query Contextualization for automated ICD coding
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Deep Gaussian Mixture Model on Multiple Interpretable Features of Fetal Heart Rate for Pregnancy Wellness
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内容著作注記
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Adverse Drug Events Detection, Extraction and Normalization from Online Comments of Chinese Patent Medicines
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Adaptive Graph Co-Attention Networks for Traffic Forecasting
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Dual-Stage Bayesian Sequence to Sequence Embeddings for Energy Demand Forecasting
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AA-LSTM: An Adversarial Autoencoder Joint Model for Prediction of Equipment Remaining Useful Life
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Data Mining of Specialized Data
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Analyzing Topic Transitions in Text-based Social Cascades using Dual-Network Hawkes Process
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内容著作注記
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HiPaR: Hierarchical Pattern-Aided Regression
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内容著作注記
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Improved Topology Extraction using Discriminative Parameter Mining of Logs
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Back to Prior Knowledge: Joint Event Causality Extraction via Convolutional Semantic Infusion
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内容著作注記
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A k-MCST based Algorithm for Discovering Core-Periphery Structures in Graphs
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内容著作注記
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Detecting Sequentially Novel Classes with Stable Generalization Ability
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Learning-based Dynamic Graph Stream Sketch
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内容著作注記
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Discovering Dense Correlated Subgraphs in Dynamic Networks
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Fake News Detection with Heterogenous Deep Graph Convolutional Network
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内容著作注記
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Incrementally Finding the Vertices Absent from the Maximum Independent Sets
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Neighbours and Kinsmen: Hateful Users Detection with Graph Neural Network
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Graph Neural Networks for Soft Semi-Supervised Learning on Hypergraphs
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A Meta-path based Graph Convolutional Network with Multi-Scale Semantic Extractions for Heterogeneous Event Classification
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Noise-Enhanced Unsupervised Link Prediction
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Weak Supervision Network Embedding for Constrained Graph Learning
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RAGA: Relation-aware Graph Attention Networks for Global Entity Alignment
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Graph Attention Networks with Positional Embeddings
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Unified Robust Training for Graph Neural Networks against Label Noise
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Graph InfoClust: Maximizing Coarse-Grain Mutual Information in Graphs
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A Deep Hybrid Pooling Architecture for Graph Classification with Hierarchical Attention
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Maximizing Explainability with SF-Lasso and Selective Inference for Video and Picture Ads. -Reliably Calibrated Isotonic Regression
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Multiple Instance Learning for Unilateral Data
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An Online Learning Algorithm for Non-Stationary Imbalanced Data by Extra-Charging Minority Class
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Locally Linear Support Vector Machines for Imbalanced Data Classification. - Low-Dimensional Representation Learning from Imbalanced Data Streams
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内容著作注記
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PhotoStylist: Altering the Style of Photos based on the Connotations of Texts
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内容著作注記
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Gazetteer-Guided Keyphrase Generation from Research Papers
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内容著作注記
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Minits-AllOcc: An Efficient Algorithm for Mining Timed Sequential Patterns
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内容著作注記
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T^3N: Harnessing Text and Temporal Tree Network for Rumor Detection on Twitter
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AngryBERT: Joint Learning Target and Emotion for Hate Speech Detection
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内容著作注記
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SCARLET: Explainable Attention based Graph Neural Network for Fake News spreader prediction
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内容著作注記
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Content matters: A GNN-based Model Combined with Text Semantics for Social Network Cascade Prediction
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内容著作注記
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TERMCast: Temporal Relation Modeling for Effective Urban Flow Forecasting
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内容著作注記
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Traffic Flow Driven Spatio-Temporal Graph Convolutional Network for Ride-hailing Demand Forecasting
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A Proximity Forest for Multivariate Time Series Classification
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C〓-Guard: A Cross-Correlation Gaining Framework for Urban Air Quality Prediction
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内容著作注記
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Simultaneous multiple POI population patternanalysis system with HDP mixture regression
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内容著作注記
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Interpretable Feature Construction for Time Series Extrinsic Regression
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内容著作注記
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SEPC: Improving Joint Extraction of Entities and Relations by Strengthening Entity Pairs Connection
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注記
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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
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NCID
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9783030757632
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本文の言語
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英語
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著者リンク
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Karlapalem, Kamal <> editor
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著者リンク
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Cheng, Hong <> editor
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著者リンク
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Ramakrishnan, Naren <> editor
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著者リンク
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Agrawal, R. K. <> editor
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著者リンク
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Reddy, P. Krishna <> editor
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著者リンク
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Srivastava, Jaideep <> editor
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著者リンク
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Chakraborty, Tanmoy <> editor
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著者リンク
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SpringerLink (Online service) <>
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分類
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DC23:006.3
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件名
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Artificial intelligence
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件名
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Data mining
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件名
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Social sciences—Data processing
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件名
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Computer networks
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件名
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Algorithms
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件名
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Artificial Intelligence
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件名
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Data Mining and Knowledge Discovery
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件名
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Computer Application in Social and Behavioral Sciences
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件名
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Computer Communication Networks
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件名
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Design and Analysis of Algorithms
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電子書籍・雑誌へアクセス
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https://doi.org/10.1007/978-3-030-75762-5
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