Advances in Knowledge Discovery and Data Mining

25th Pacific-Asia Conference, PAKDD 2021, Virtual Event, May 11–14, 2021, Proceedings, Part II

Häftad, Engelska, 2021

Av Kamal Karlapalem, Hong Cheng, Naren Ramakrishnan, R. K. Agrawal, P. Krishna Reddy, Jaideep Srivastava, Tanmoy Chakraborty

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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.

Produktinformation

Utgivningsdatum2021-05-08
Mått155 x 235 x 43 mm
Vikt1 188 g
FormatHäftad
SpråkEngelska
SerieLecture Notes in Computer Science
Antal sidor774
FörlagSpringer Nature Switzerland AG
ISBN9783030757649

Tillhör följande kategorier

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.