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_a10.1007/978-3-030-75765-6 _2doi |
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| 035 | _a(DE-He213)978-3-030-75765-6 | ||
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_aQA76.9.D343 _b.A383 2021 |
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_aAdvances in Knowledge Discovery and Data Mining : _b25th Pacific-Asia Conference, PAKDD 2021, Virtual Event, May 11–14, 2021, Proceedings, Part II / _cedited by Kamal Karlapalem, Hong Cheng, Naren Ramakrishnan, R. K. Agrawal, P. Krishna Reddy, Jaideep Srivastava, Tanmoy Chakraborty. |
| 250 | _a1st ed. 2021. | ||
| 264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2021. |
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| 300 | _a1 online resource (XXVI, 774 p. 30 illus.) | ||
| 336 |
_atext _btxt _2rdacontent |
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| 337 |
_acomputer _bc _2rdamedia |
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| 338 |
_aonline resource _bcr _2rdacarrier |
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| 490 | 0 |
_aLecture Notes in Artificial Intelligence, _x2945-9141 ; _v12713 |
|
| 505 | 0 | _aClassical 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. | |
| 520 | _aThe 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. | ||
| 650 | 0 | _aArtificial intelligence. | |
| 650 | 0 |
_aSocial sciences _xData processing. |
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| 650 | 0 |
_aEducation _xData processing. _985469 |
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| 650 | 0 |
_aApplication software. _94694 |
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| 650 | 0 |
_aImage processing _xDigital techniques. _9118 |
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| 650 | 0 |
_aComputer vision. _92455 |
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| 650 | 1 | 4 | _aArtificial Intelligence. |
| 650 | 2 | 4 | _aComputer Application in Social and Behavioral Sciences. |
| 650 | 2 | 4 | _aComputers and Education. |
| 650 | 2 | 4 | _aComputer and Information Systems Applications. |
| 650 | 2 | 4 | _aComputer Imaging, Vision, Pattern Recognition and Graphics. |
| 655 | 7 |
_aElectronic books _2local _92032 |
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| 700 | 1 |
_aKamalakar, Karlapalem, _eeditor |
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| 776 | 0 | 8 | _z3-030-75764-1 |
| 830 | 0 |
_aLecture Notes in Artificial Intelligence, _x2945-9141 ; _v12713 |
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| 856 |
_3Springerlink _uhttps://link.springer.com/book/10.1007/978-3-030-75765-6 _zOnline access link to the resource |
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