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Autor Agrawal, R. K. |
Documentos disponibles escritos por este autor (3)
Crear una solicitud de compra Refinar búsquedaAdvances in Knowledge Discovery and Data Mining / Karlapalem, Kamal ; Cheng, Hong ; Ramakrishnan, Naren ; Agrawal, R. K. ; Reddy, P. Krishna ; Srivastava, Jaideep ; Chakraborty, Tanmoy
TÃtulo : Advances in Knowledge Discovery and Data Mining : 25th Pacific-Asia Conference, PAKDD 2021, Virtual Event, May 11–14, 2021, Proceedings, Part I / Tipo de documento: documento electrónico Autores: Karlapalem, Kamal, ; Cheng, Hong, ; Ramakrishnan, Naren, ; Agrawal, R. K., ; Reddy, P. Krishna, ; Srivastava, Jaideep, ; Chakraborty, Tanmoy, Mención de edición: 1 ed. Editorial: [s.l.] : Springer Fecha de publicación: 2021 Número de páginas: XXXV, 834 p. 30 ilustraciones ISBN/ISSN/DL: 978-3-030-75762-5 Nota general: Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos. Idioma : Inglés (eng) Palabras clave: Inteligencia artificial Procesamiento de datos Ciencias sociales Red de computadoras Algoritmos MinerÃa de datos y descubrimiento de conocimientos Aplicación informática en ciencias sociales y del comportamiento. Redes de comunicación informática Diseño y Análisis de Algoritmos Clasificación: 006.3 Resumen: El conjunto de tres volúmenes LNAI 12712-12714 constituye las actas de la 25.ª Conferencia de Asia PacÃfico sobre avances en el descubrimiento de conocimientos y la minerÃa de datos, PAKDD 2021, que se celebró del 11 al 14 de mayo de 2021. Los 157 artÃculos incluidos en las actas fueron cuidadosamente revisado y seleccionado de un total de 628 presentaciones. Se organizaron en secciones temáticas de la siguiente manera: Parte I: Aplicaciones del descubrimiento de conocimientos y extracción de datos especializados; Parte II: MinerÃa de datos clásica; teorÃa y principios de minerÃa de datos; sistemas de recomendación; y análisis de texto; Parte III: Aprendizaje e incorporación de representaciones, y aprendizaje a partir de datos. Nota de contenido: 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: HatefulUsers 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. Tipo de medio : Computadora 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. Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] Advances in Knowledge Discovery and Data Mining : 25th Pacific-Asia Conference, PAKDD 2021, Virtual Event, May 11–14, 2021, Proceedings, Part I / [documento electrónico] / Karlapalem, Kamal, ; Cheng, Hong, ; Ramakrishnan, Naren, ; Agrawal, R. K., ; Reddy, P. Krishna, ; Srivastava, Jaideep, ; Chakraborty, Tanmoy, . - 1 ed. . - [s.l.] : Springer, 2021 . - XXXV, 834 p. 30 ilustraciones.
ISBN : 978-3-030-75762-5
Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos.
Idioma : Inglés (eng)
Palabras clave: Inteligencia artificial Procesamiento de datos Ciencias sociales Red de computadoras Algoritmos MinerÃa de datos y descubrimiento de conocimientos Aplicación informática en ciencias sociales y del comportamiento. Redes de comunicación informática Diseño y Análisis de Algoritmos Clasificación: 006.3 Resumen: El conjunto de tres volúmenes LNAI 12712-12714 constituye las actas de la 25.ª Conferencia de Asia PacÃfico sobre avances en el descubrimiento de conocimientos y la minerÃa de datos, PAKDD 2021, que se celebró del 11 al 14 de mayo de 2021. Los 157 artÃculos incluidos en las actas fueron cuidadosamente revisado y seleccionado de un total de 628 presentaciones. Se organizaron en secciones temáticas de la siguiente manera: Parte I: Aplicaciones del descubrimiento de conocimientos y extracción de datos especializados; Parte II: MinerÃa de datos clásica; teorÃa y principios de minerÃa de datos; sistemas de recomendación; y análisis de texto; Parte III: Aprendizaje e incorporación de representaciones, y aprendizaje a partir de datos. Nota de contenido: 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: HatefulUsers 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. Tipo de medio : Computadora 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. Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...]
TÃtulo : Advances in Knowledge Discovery and Data Mining : 25th Pacific-Asia Conference, PAKDD 2021, Virtual Event, May 11–14, 2021, Proceedings, Part II / Tipo de documento: documento electrónico Autores: Karlapalem, Kamal, ; Cheng, Hong, ; Ramakrishnan, Naren, ; Agrawal, R. K., ; Reddy, P. Krishna, ; Srivastava, Jaideep, ; Chakraborty, Tanmoy, Mención de edición: 1 ed. Editorial: [s.l.] : Springer Fecha de publicación: 2021 Número de páginas: XXVI, 774 p. 30 ilustraciones ISBN/ISSN/DL: 978-3-030-75765-6 Nota general: Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos. Idioma : Inglés (eng) Palabras clave: Inteligencia artificial Ciencias sociales Software de la aplicacion Procesamiento de imágenes Visión por computador Aplicación informática en ciencias sociales y del comportamiento. Computadoras y Educación Aplicaciones informáticas y de sistemas de información Imágenes por computadora visión reconocimiento de patrones y gráficos Clasificación: 006.3 Resumen: El conjunto de tres volúmenes LNAI 12712-12714 constituye las actas de la 25.ª Conferencia de Asia PacÃfico sobre avances en el descubrimiento de conocimientos y la minerÃa de datos, PAKDD 2021, que se celebró del 11 al 14 de mayo de 2021. Los 157 artÃculos incluidos en las actas fueron cuidadosamente revisado y seleccionado de un total de 628 presentaciones. Se organizaron en secciones temáticas de la siguiente manera: Parte I: Aplicaciones del descubrimiento de conocimientos y extracción de datos especializados; Parte II: MinerÃa de datos clásica; teorÃa y principios de minerÃa de datos; sistemas de recomendación; y análisis de texto; Parte III: Aprendizaje e incorporación de representaciones, y aprendizaje a partir de datos. Nota de contenido: Classical Data Mining,. Mining Frequent Patterns from Hypergraph Databases -- Discriminating Frequent Pattern based Supervised Graph Embedding for Classification -- Mining Sequential Patterns in Uncertain Databases Using Hierarchical Index Structure -- Similarity Forest Revisited: a Swiss Army Knife for Machine Learning -- Discriminative Representation Learning for Cross-domain Sentiment Classification -- SAGCN: Towards Structure-Aware Deep Graph Convolutional Networks on Node Classification -- Hierarchical Learning of Dependent Concepts for Human Activity Recognition -- Improving Short Text Classification Using Context-Sensitive Representations and Content-Aware Extended Topic Knowledge -- A Novel Method for Offline Handwritten Chinese Character Recognition under the Guidance of Print -- Upgraded Attention-based Local FeatureLearning Block for speech emotion recognition -- Memorization in Deep Neural Networks: Does the Loss Function matter -- Gaussian Soft Decision Trees for Interpretable Feature-Based Classification -- Efficient Nodes Representation Learning with Residual Feature Propagation -- Progressive AutoSpeech: An efficient and general framework for automatic speech classification -- CrowdTeacher: Robust Co-teaching with Noisy Answers & Sample-specific Perturbations for Tabular Data -- Effective and Adaptive Multi-metric Refined Similarity Graph Fusion for Multi-view Clustering -- aHCQ: Adaptive Hierarchical Clustering based Quantization Framework for Deep Neural Networks -- Maintaining Consistency with Constraints: a Constrained Deep Clustering method -- Data Mining Theory and Principles -- Towards multi-label Feature selection by Instance and Label Selections -- FARF: A Fair and Adaptive Random Forests Classifier -- Sparse Spectrum Gaussian Process for Bayesian Optimization -- Densely Connected Graph Attention Network based on Iterative Path Reasoning for Document-level Relation Extraction -- Causal Inference Using Global Forecasting Models for Counterfactual Prediction. -CED-BGFN: Chinese Event Detection via Bidirectional Glyph-aware Dynamic Fusion Network -- Learning Finite Automata with Shuffle -- Active Learning based Similarity Filtering for Efficient and Effective Record Linkage -- Stratified Sampling for Extreme Multi-Label Data -- Vertical Federated Learning for Higher-order Factorization Machines -- dK-Projection: Publishing Graph Joint degree distribution with Node Differential Privacy -- Recommender Systems -- Improving Sequential Recommendation with Attribute-augmented Graph Neural Networks -- Exploring Implicit Relationships in Social Network for Recommendation Systems -- Transferable Contextual Bandits with Prior Observations -- Modeling Hierarchical Intents and Selective Current Interest for Session-based Recommendation -- A Finetuned language model for Recommending cQA-QAs for enriching Textbooks -- XCrossNet: Feature Structure-Oriented Learning for Click-Through Rate Prediction -- Learning Multiclass Classifier Under Noisy Bandit Feedback -- Diversify orNot: Dynamic Diversification for Personalized Recommendation -- Multi-criteria and Review-based Overall Rating Prediction -- W2FM: The Doubly-Warped Factorization Machine -- Causal Combinatorial Factorization Machines for Set-wise Recommendation -- Transformer-based Multi-task Learning for Queuing Time Aware Next POI Recommendation -- Joint Modeling Dynamic Preferences of Users and Items Using Reviews for Sequential Recommendation -- Box4Rec: Box Embedding for Sequential Recommendation -- UKIRF: An Item Rejection Framework for Improving Negative Items Sampling in One-Class Collaborative Filtering -- IACN: Influence-aware and Attention-based Co-evolutionary Network for Recommendation -- Nonlinear Matrix Factorization via Neighbor Embedding -- Deconfounding representation learning based on user interactions in Recommendation Systems -- Personalized Regularization Learning for Fairer Matrix Factorization -- Instance Selection for Online Updating in Dynamic Recommender Environments -- Text Analytics.-Fusing Essential Knowledge for Text-Based Open-Domain Question Answering. - TSSE-DMM: Topic Modeling for Short Texts based on Topic Subdivision and Semantic Enhancement -- SILVER: Generating Persuasive Chinese Product Pitch -- Capturing SQL Query Overlapping via SubtreeCopy for Cross-domain Context-dependent SQLGeneration -- HScodeNet: Combining Hierarchical Sequential and Global Spatial Information of Text for Commodity HS Code Classification -- PLVCG: A Pretraining Based Model for Live Video Comment Generation -- Inducing Rich Interaction Structures between Words for Document-level Event Argument Extraction -- Exploiting Relevant Hyperlinks in Knowledge Base for Entity Linking -- TANTP: Conversational Emotion Recognition Using Tree-Based Attention Networks with Transformer Pre-training -- Semantic-syntax Cascade Injection Model for Aspect Sentiment Triple Extraction -- Modeling Inter-Aspect Relationship with Conjunction for Aspect-based Sentiment Analysis. Tipo de medio : Computadora 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. Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] Advances in Knowledge Discovery and Data Mining : 25th Pacific-Asia Conference, PAKDD 2021, Virtual Event, May 11–14, 2021, Proceedings, Part II / [documento electrónico] / Karlapalem, Kamal, ; Cheng, Hong, ; Ramakrishnan, Naren, ; Agrawal, R. K., ; Reddy, P. Krishna, ; Srivastava, Jaideep, ; Chakraborty, Tanmoy, . - 1 ed. . - [s.l.] : Springer, 2021 . - XXVI, 774 p. 30 ilustraciones.
ISBN : 978-3-030-75765-6
Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos.
Idioma : Inglés (eng)
Palabras clave: Inteligencia artificial Ciencias sociales Software de la aplicacion Procesamiento de imágenes Visión por computador Aplicación informática en ciencias sociales y del comportamiento. Computadoras y Educación Aplicaciones informáticas y de sistemas de información Imágenes por computadora visión reconocimiento de patrones y gráficos Clasificación: 006.3 Resumen: El conjunto de tres volúmenes LNAI 12712-12714 constituye las actas de la 25.ª Conferencia de Asia PacÃfico sobre avances en el descubrimiento de conocimientos y la minerÃa de datos, PAKDD 2021, que se celebró del 11 al 14 de mayo de 2021. Los 157 artÃculos incluidos en las actas fueron cuidadosamente revisado y seleccionado de un total de 628 presentaciones. Se organizaron en secciones temáticas de la siguiente manera: Parte I: Aplicaciones del descubrimiento de conocimientos y extracción de datos especializados; Parte II: MinerÃa de datos clásica; teorÃa y principios de minerÃa de datos; sistemas de recomendación; y análisis de texto; Parte III: Aprendizaje e incorporación de representaciones, y aprendizaje a partir de datos. Nota de contenido: Classical Data Mining,. Mining Frequent Patterns from Hypergraph Databases -- Discriminating Frequent Pattern based Supervised Graph Embedding for Classification -- Mining Sequential Patterns in Uncertain Databases Using Hierarchical Index Structure -- Similarity Forest Revisited: a Swiss Army Knife for Machine Learning -- Discriminative Representation Learning for Cross-domain Sentiment Classification -- SAGCN: Towards Structure-Aware Deep Graph Convolutional Networks on Node Classification -- Hierarchical Learning of Dependent Concepts for Human Activity Recognition -- Improving Short Text Classification Using Context-Sensitive Representations and Content-Aware Extended Topic Knowledge -- A Novel Method for Offline Handwritten Chinese Character Recognition under the Guidance of Print -- Upgraded Attention-based Local FeatureLearning Block for speech emotion recognition -- Memorization in Deep Neural Networks: Does the Loss Function matter -- Gaussian Soft Decision Trees for Interpretable Feature-Based Classification -- Efficient Nodes Representation Learning with Residual Feature Propagation -- Progressive AutoSpeech: An efficient and general framework for automatic speech classification -- CrowdTeacher: Robust Co-teaching with Noisy Answers & Sample-specific Perturbations for Tabular Data -- Effective and Adaptive Multi-metric Refined Similarity Graph Fusion for Multi-view Clustering -- aHCQ: Adaptive Hierarchical Clustering based Quantization Framework for Deep Neural Networks -- Maintaining Consistency with Constraints: a Constrained Deep Clustering method -- Data Mining Theory and Principles -- Towards multi-label Feature selection by Instance and Label Selections -- FARF: A Fair and Adaptive Random Forests Classifier -- Sparse Spectrum Gaussian Process for Bayesian Optimization -- Densely Connected Graph Attention Network based on Iterative Path Reasoning for Document-level Relation Extraction -- Causal Inference Using Global Forecasting Models for Counterfactual Prediction. -CED-BGFN: Chinese Event Detection via Bidirectional Glyph-aware Dynamic Fusion Network -- Learning Finite Automata with Shuffle -- Active Learning based Similarity Filtering for Efficient and Effective Record Linkage -- Stratified Sampling for Extreme Multi-Label Data -- Vertical Federated Learning for Higher-order Factorization Machines -- dK-Projection: Publishing Graph Joint degree distribution with Node Differential Privacy -- Recommender Systems -- Improving Sequential Recommendation with Attribute-augmented Graph Neural Networks -- Exploring Implicit Relationships in Social Network for Recommendation Systems -- Transferable Contextual Bandits with Prior Observations -- Modeling Hierarchical Intents and Selective Current Interest for Session-based Recommendation -- A Finetuned language model for Recommending cQA-QAs for enriching Textbooks -- XCrossNet: Feature Structure-Oriented Learning for Click-Through Rate Prediction -- Learning Multiclass Classifier Under Noisy Bandit Feedback -- Diversify orNot: Dynamic Diversification for Personalized Recommendation -- Multi-criteria and Review-based Overall Rating Prediction -- W2FM: The Doubly-Warped Factorization Machine -- Causal Combinatorial Factorization Machines for Set-wise Recommendation -- Transformer-based Multi-task Learning for Queuing Time Aware Next POI Recommendation -- Joint Modeling Dynamic Preferences of Users and Items Using Reviews for Sequential Recommendation -- Box4Rec: Box Embedding for Sequential Recommendation -- UKIRF: An Item Rejection Framework for Improving Negative Items Sampling in One-Class Collaborative Filtering -- IACN: Influence-aware and Attention-based Co-evolutionary Network for Recommendation -- Nonlinear Matrix Factorization via Neighbor Embedding -- Deconfounding representation learning based on user interactions in Recommendation Systems -- Personalized Regularization Learning for Fairer Matrix Factorization -- Instance Selection for Online Updating in Dynamic Recommender Environments -- Text Analytics.-Fusing Essential Knowledge for Text-Based Open-Domain Question Answering. - TSSE-DMM: Topic Modeling for Short Texts based on Topic Subdivision and Semantic Enhancement -- SILVER: Generating Persuasive Chinese Product Pitch -- Capturing SQL Query Overlapping via SubtreeCopy for Cross-domain Context-dependent SQLGeneration -- HScodeNet: Combining Hierarchical Sequential and Global Spatial Information of Text for Commodity HS Code Classification -- PLVCG: A Pretraining Based Model for Live Video Comment Generation -- Inducing Rich Interaction Structures between Words for Document-level Event Argument Extraction -- Exploiting Relevant Hyperlinks in Knowledge Base for Entity Linking -- TANTP: Conversational Emotion Recognition Using Tree-Based Attention Networks with Transformer Pre-training -- Semantic-syntax Cascade Injection Model for Aspect Sentiment Triple Extraction -- Modeling Inter-Aspect Relationship with Conjunction for Aspect-based Sentiment Analysis. Tipo de medio : Computadora 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. Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...]
TÃtulo : Advances in Knowledge Discovery and Data Mining : 25th Pacific-Asia Conference, PAKDD 2021, Virtual Event, May 11–14, 2021, Proceedings, Part III / Tipo de documento: documento electrónico Autores: Karlapalem, Kamal, ; Cheng, Hong, ; Ramakrishnan, Naren, ; Agrawal, R. K., ; Reddy, P. Krishna, ; Srivastava, Jaideep, ; Chakraborty, Tanmoy, Mención de edición: 1 ed. Editorial: [s.l.] : Springer Fecha de publicación: 2021 Número de páginas: XXIII, 434 p. 142 ilustraciones, 117 ilustraciones en color. ISBN/ISSN/DL: 978-3-030-75768-7 Nota general: Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos. Idioma : Inglés (eng) Palabras clave: Inteligencia artificial Ciencias sociales Algoritmos Informática Visión por computador Aplicación informática en ciencias sociales y del comportamiento. Diseño y Análisis de Algoritmos Computadoras y Educación Matemáticas de la Computación Clasificación: 006.3 Resumen: El conjunto de tres volúmenes LNAI 12712-12714 constituye las actas de la 25.ª Conferencia de Asia PacÃfico sobre avances en el descubrimiento de conocimientos y la minerÃa de datos, PAKDD 2021, que se celebró del 11 al 14 de mayo de 2021. Los 157 artÃculos incluidos en las actas fueron cuidadosamente revisado y seleccionado de un total de 628 presentaciones. Se organizaron en secciones temáticas de la siguiente manera: Parte I: Aplicaciones del descubrimiento de conocimientos y extracción de datos especializados; Parte II: MinerÃa de datos clásica; teorÃa y principios de minerÃa de datos; sistemas de recomendación; y análisis de texto; Parte III: Aprendizaje e incorporación de representaciones, y aprendizaje a partir de datos. Nota de 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. Tipo de medio : Computadora 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. Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] Advances in Knowledge Discovery and Data Mining : 25th Pacific-Asia Conference, PAKDD 2021, Virtual Event, May 11–14, 2021, Proceedings, Part III / [documento electrónico] / Karlapalem, Kamal, ; Cheng, Hong, ; Ramakrishnan, Naren, ; Agrawal, R. K., ; Reddy, P. Krishna, ; Srivastava, Jaideep, ; Chakraborty, Tanmoy, . - 1 ed. . - [s.l.] : Springer, 2021 . - XXIII, 434 p. 142 ilustraciones, 117 ilustraciones en color.
ISBN : 978-3-030-75768-7
Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos.
Idioma : Inglés (eng)
Palabras clave: Inteligencia artificial Ciencias sociales Algoritmos Informática Visión por computador Aplicación informática en ciencias sociales y del comportamiento. Diseño y Análisis de Algoritmos Computadoras y Educación Matemáticas de la Computación Clasificación: 006.3 Resumen: El conjunto de tres volúmenes LNAI 12712-12714 constituye las actas de la 25.ª Conferencia de Asia PacÃfico sobre avances en el descubrimiento de conocimientos y la minerÃa de datos, PAKDD 2021, que se celebró del 11 al 14 de mayo de 2021. Los 157 artÃculos incluidos en las actas fueron cuidadosamente revisado y seleccionado de un total de 628 presentaciones. Se organizaron en secciones temáticas de la siguiente manera: Parte I: Aplicaciones del descubrimiento de conocimientos y extracción de datos especializados; Parte II: MinerÃa de datos clásica; teorÃa y principios de minerÃa de datos; sistemas de recomendación; y análisis de texto; Parte III: Aprendizaje e incorporación de representaciones, y aprendizaje a partir de datos. Nota de 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. Tipo de medio : Computadora 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. Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...]
