| Description |
1 online resource (xxvi, 774 pages) : illustrations |
| Series |
Lecture notes in artificial intelligence |
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Lecture notes in computer science ; 12713 |
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LNCS sublibrary, SL 7, Artificial intelligence |
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Lecture notes in computer science. Lecture notes in artificial intelligence.
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Lecture notes in computer science ; 12713.
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LNCS sublibrary. SL 7, Artificial intelligence.
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| Contents |
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 or Not: 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 |
| 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 |
| Notes |
Includes author index |
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Online resource; title from PDF title page (SpringerLink, viewed May 10, 2021) |
| Subject |
Data mining -- Congresses
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Artificial intelligence -- Congresses
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Artificial intelligence
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Data mining
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| Genre/Form |
proceedings (reports)
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Conference papers and proceedings
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Conference papers and proceedings.
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Actes de congrès.
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| Form |
Electronic book
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| Author |
Karlapalem, Kamal, editor
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Cheng, Hong (Engineering teacher), editor
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Ramakrishnan, Naren, editor
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Agrawal, R. K., editor
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Reddy, P. Krishna (Polepalli Krishna), editor
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Srivastava, Jaideep, editor.
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Chakraborty, Tanmoy, editor
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| ISBN |
9783030757656 |
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303075765X |
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