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Advances in Knowledge Discovery and Data Mining [25th Pacific-Asia Conference, PAKDD 2021, Virtual Event, May 11{u2013}14, 2021, Proceedings, Part III

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

Monografía

monografia Rebiun28141396 https://catalogo.rebiun.org/rebiun/record/Rebiun28141396 cr nn 008mamaa 210507s2021 gw | s |||| 0|eng d 9783030757687 10.1007/978-3-030-75768-7 doi UPNA0540337 UPVA 997435554603706 UAM 991008052757004211 UPM 991005908037804212 CBUC 991004876535306711 CBUC 991000725495906712 CBUC 991003519757606714 CBUC 991010401385706709 CBUC 991004008662706713 CBUC 991009899987106719 CBUC 991012520289206708 CBUC 991010401385706709 UCAR 991008198118704213 UR0514842 UYQ thema UYQ bicssc COM004000 bisacsh Advances in Knowledge Discovery and Data Mining Recurso electrónico] :] 25th Pacific-Asia Conference, PAKDD 2021, Virtual Event, May 11{u2013}14, 2021, Proceedings, Part III edited by Kamal Karlapalem, Hong Cheng, Naren Ramakrishnan, R. K. Agrawal, P. Krishna Reddy, Jaideep Srivastava, Tanmoy Chakraborty 1st ed. 2021 Cham Springer International Publishing Imprint: Springer 2021 Cham Cham Springer International Publishing Imprint: Springer XXIII, 434 p. 142 illus., 117 illus. in color. online resource XXIII, 434 p. 142 illus., 117 illus. in color. Text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Lecture Notes in Artificial Intelligence 12714 Representation Learning and Embedding -- Episode Adaptive Embedding Networks for Few-shot Learning -- Universal Representation for Code -- Self-supervised Adaptive Aggregator Learning on Graph -- A Fast Algorithm for Simultaneous Sparse Approximation -- STEPs-RL: Speech-Text Entanglement for Phonetically Sound Representation Learning -- RW-GCN: Training Graph Convolution Networks with biased random walk for Semi-Supervised Classification -- Loss-aware Pattern Inference: A Correction on the Wrongly Claimed Limitations of Embedding Models -- SST-GNN: Simplified Spatio-temporal Traffic forecasting model using Graph Neural Network -- VIKING: Adversarial Attack on Network Embeddings via Supervised Network Poisoning -- Self-supervised Graph Representation Learning with Variational Inference -- Manifold Approximation and Projection by Maximizing Graph Information -- Learning Attention-based Translational Knowledge Graph Embedding via Nonlinear Dynamic Mapping -- Multi-Grained Dependency Graph Neural Network for Chinese Open Information Extraction -- Human-Understandable Decision Making for Visual Recognition -- LightCAKE: A Lightweight Framework for Context-Aware Knowledge Graph Embedding -- Transferring Domain Knowledge with an Adviser in Continuous Tasks -- Inferring Hierarchical Mixture Structures: A Bayesian Nonparametric Approach -- Quality Control for Hierarchical Classification with Incomplete Annotations -- Learning from Data -- Learning Discriminative Features using Multi-label Dual Space -- AutoCluster: Meta-learning Based Ensemble Method for Automated Unsupervised Clustering -- BanditRank: Learning to Rank Using Contextual Bandits -- A compressed and accelerated SegNet for plant leaf disease segmentation: A Differential Evolution based approach -- Meta-Context Transformers for Domain-Specific Response Generation -- A Multi-task Kernel Learning Algorithm for Survival Analysis -- Meta-data Augmentation based Search Strategy through Generative Adversarial Network for AutoML Model Selection -- Tree-Capsule: Tree-Structured Capsule Network for Improving Relation Extraction -- Rule Injection-based Generative Adversarial Imitation Learning for Knowledge Graph Reasoning -- Hierarchical Self Attention Based Autoencoder for Open-Set Human Activity Recognition -- Reinforced Natural Language Inference for Distantly Supervised Relation Classification -- SaGCN: Structure-aware Graph Convolution Network for Document-level Relation Extraction -- Addressing the class imbalance problem in medical image segmentation via accelerated Tversky loss function -- Incorporating Relational Knowledge in Explainable Fake News Detection -- Incorporating Syntactic Information into Relation Representations for Enhanced Relation Extraction 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 Artificial intelligence Application software Algorithms Education{u2014}Data processing Computer science{u2014}Mathematics Optical data processing Artificial Intelligence Computer Appl. in Social and Behavioral Sciences Algorithm Analysis and Problem Complexity Computers and Education Mathematics of Computing Image Processing and Computer Vision Karlapalem, Kamal. editor. https://orcid.org/0000-0003-2528-7979. edt. http://id.loc.gov/vocabulary/relators/edt Cheng, Hong editor. edt. http://id.loc.gov/vocabulary/relators/edt Ramakrishnan, Naren. editor. edt. http://id.loc.gov/vocabulary/relators/edt Agrawal, R. K. editor. edt. http://id.loc.gov/vocabulary/relators/edt Reddy, P. Krishna. editor. https://orcid.org/0000-0003-1238-5174. edt. http://id.loc.gov/vocabulary/relators/edt Srivastava, Jaideep. editor. edt. http://id.loc.gov/vocabulary/relators/edt Chakraborty, Tanmoy. editor. https://orcid.org/0000-0002-0210-0369. edt. http://id.loc.gov/vocabulary/relators/edt SpringerLink Book Series (Online Service) Lecture Notes in Artificial Intelligence 12714

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Préstamo interbibliotecario

Formato:

Título:

Advances in Knowledge Discovery and Data Mining [ Recurso electrónico] :] 25th Pacific-Asia Conference, PAKDD 2021, Virtual Event, May 11{u2013}14, 2021, Proceedings, Part III / edited by Kamal Karlapalem, Hong Cheng, Naren Ramakrishnan, R. K. Agrawal, P. Krishna Reddy, Jaideep Srivastava, Tanmoy Chakraborty

Edición:

1st ed. 2021

Editorial:

Cham : Springer International Publishing : Imprint: Springer, 2021

Descripción física:

XXIII, 434 p. 142 illus., 117 illus. in color. : online resource

Mención de serie:

Lecture Notes in Artificial Intelligence ; 12714

Contenido:

Representation Learning and Embedding -- Episode Adaptive Embedding Networks for Few-shot Learning -- Universal Representation for Code -- Self-supervised Adaptive Aggregator Learning on Graph -- A Fast Algorithm for Simultaneous Sparse Approximation -- STEPs-RL: Speech-Text Entanglement for Phonetically Sound Representation Learning -- RW-GCN: Training Graph Convolution Networks with biased random walk for Semi-Supervised Classification -- Loss-aware Pattern Inference: A Correction on the Wrongly Claimed Limitations of Embedding Models -- SST-GNN: Simplified Spatio-temporal Traffic forecasting model using Graph Neural Network -- VIKING: Adversarial Attack on Network Embeddings via Supervised Network Poisoning -- Self-supervised Graph Representation Learning with Variational Inference -- Manifold Approximation and Projection by Maximizing Graph Information -- Learning Attention-based Translational Knowledge Graph Embedding via Nonlinear Dynamic Mapping -- Multi-Grained Dependency Graph Neural Network for Chinese Open Information Extraction -- Human-Understandable Decision Making for Visual Recognition -- LightCAKE: A Lightweight Framework for Context-Aware Knowledge Graph Embedding -- Transferring Domain Knowledge with an Adviser in Continuous Tasks -- Inferring Hierarchical Mixture Structures: A Bayesian Nonparametric Approach -- Quality Control for Hierarchical Classification with Incomplete Annotations -- Learning from Data -- Learning Discriminative Features using Multi-label Dual Space -- AutoCluster: Meta-learning Based Ensemble Method for Automated Unsupervised Clustering -- BanditRank: Learning to Rank Using Contextual Bandits -- A compressed and accelerated SegNet for plant leaf disease segmentation: A Differential Evolution based approach -- Meta-Context Transformers for Domain-Specific Response Generation -- A Multi-task Kernel Learning Algorithm for Survival Analysis -- Meta-data Augmentation based Search Strategy through Generative Adversarial Network for AutoML Model Selection -- Tree-Capsule: Tree-Structured Capsule Network for Improving Relation Extraction -- Rule Injection-based Generative Adversarial Imitation Learning for Knowledge Graph Reasoning -- Hierarchical Self Attention Based Autoencoder for Open-Set Human Activity Recognition -- Reinforced Natural Language Inference for Distantly Supervised Relation Classification -- SaGCN: Structure-aware Graph Convolution Network for Document-level Relation Extraction -- Addressing the class imbalance problem in medical image segmentation via accelerated Tversky loss function -- Incorporating Relational Knowledge in Explainable Fake News Detection -- Incorporating Syntactic Information into Relation Representations for Enhanced Relation Extraction

ISBN:

9783030757687

Materia: