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Advances in Knowledge Discovery and Data Mining: 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, Osaka, Japan, May ... (Lecture Notes in Computer Science, 13937) - Softcover
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The 4-volume set LNAI 13935 - 13938 constitutes the proceedings of the 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, which took place in Osaka, Japan during May 25–28, 2023.
The 143 papers presented in these proceedings were carefully reviewed and selected from 813 submissions. They deal with new ideas, original research results, and practical development experiences from all KDD related areas, including data mining, data warehousing, machine learning, artificial intelligence, databases, statistics, knowledge engineering, big data technologies, and foundations.
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Advances in Knowledge Discovery and Data Mining (eng)
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Advances in Knowledge Discovery and Data Mining : 27th Pacific-asia Conference on Knowledge Discovery and Data Mining, Pakdd 2023, Osaka, Japan, May 25-28, 2023, Proceedings
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Advances in Knowledge Discovery and Data Mining
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Springer Nature Switzerland Mai 2023, 2023
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ISBN 13: 9783031333798
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The 4-volume set LNAI 13935 - 13938 constitutes the proceedings of the27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, which took place in Osaka, Japan during May 25-28, 2023.The 143 papers presented in these proceedings were carefully reviewed and selected from 813 submissions. They deal withnew ideas, original research results, and practical development experiences from all KDD related areas, including data mining, data warehousing, machine learning, artificial intelligence, databases, statistics, knowledge engineering, big data technologies, and foundations. 436 pp. Englisch. Seller Inventory # 9783031333798
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Advances in Knowledge Discovery and Data Mining : 27th Pacific-asia Conference on Knowledge Discovery and Data Mining, Pakdd 2023, Osaka, Japan, May 25-28, 2023, Proceedings
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Advances in Knowledge Discovery and Data Mining
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ISBN 10: 3031333799
ISBN 13: 9783031333798
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Advances in Knowledge Discovery and Data Mining: 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, Osaka, Japan, May ... (Lecture Notes in Computer Science, 13937)
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Advances in Knowledge Discovery and Data Mining | 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, Osaka, Japan, May 25-28, 2023, Proceedings, Part III
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Taschenbuch. Condition: Neu. Advances in Knowledge Discovery and Data Mining | 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, Osaka, Japan, May 25-28, 2023, Proceedings, Part III | Hisashi Kashima (u. a.) | Taschenbuch | Lecture Notes in Computer Science | xvi | Englisch | 2023 | Springer | EAN 9783031333798 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. Seller Inventory # 126842560
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Advances in Knowledge Discovery and Data Mining : 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, Osaka, Japan, May 25-28, 2023, Proceedings, Part III
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - The 4-volume set LNAI 13935 - 13938 constitutes the proceedings of the27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, which took place in Osaka, Japan during May 25-28, 2023.The 143 papers presented in these proceedings were carefully reviewed and selected from 813 submissions. They deal withnew ideas, original research results, and practical development experiences from all KDD related areas, including data mining, data warehousing, machine learning, artificial intelligence, databases, statistics, knowledge engineering, big data technologies, and foundations. Seller Inventory # 9783031333798
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Advances in Knowledge Discovery and Data Mining
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ISBN 10: 3031333799
ISBN 13: 9783031333798
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Big data.- Toward Explainable Recommendation Via Counterfactual Reasoning.- Online Volume Optimization for Notifications via Long Short-Term Value Modeling.- Discovering Geo-referenced Frequent Patterns in Uncertain Geo-referenced Transactional Databases.- Financial data.- Joint Latent Topic Discovery and Expectation Modeling for Financial Markets.- Let the model make financial senses: a Text2Text generative approach for financial complaint identification.- Information retrieval and search.- Web-scale Semantic Product Search With Large Language Models.- Multi-task learning based Keywords weighted Siamese Model for semantic retrieval.- Relation-Aware Network with Attention-Based Loss for Few-Shot Knowledge Graph Completion.- MFBE: Leveraging Multi-Field Information of FAQs for Efficient Dense Retrieval.- Isotropic Representation Can Improve Dense Retrieval.- Knowledge-Enhanced Prototypical Network with Structural Semantics forFew-Shot Relation Classification.- Internet of Things.- MIDFA : Memory-Based Instance Division and Feature Aggregation Network for Video Object Detection.- Medical and biological data.- Vision Transformers for Small Histological Datasets learned through Knowledge Distillation.- Cascaded Latent Diffusion Models for High-Resolution Chest X-ray Synthesis.- DKFM: Dual Knowledge-guided Fusion Model for Drug Recommendation.- Hierarchical Graph Neural Network for Patient Treatment Preference Prediction with External Knowledge.- Multimedia and multimodal data.- An Extended Variational Mode Decomposition Algorithm Developed Speech Emotion Recognition Performance.- Dynamically-Scaled Deep Canonical Correlation Analysis.- TCR: Short Video Title Generation and Cover Selection with Attention Refinement.- ItrievalKD: An Iterative Retrieval Framework Assisted with Knowledge Distillation for Noisy Text-to-Image Retrieval.- Recommender systems.- Semantic Relation Transfer for Non-overlapped Cross-domain Recommendations.- Interest Driven Graph Structure Learning for Session-Based Recommendation.- Multi-behavior Guided Temporal Graph Attention Network for Recommendation.- Pure Spectral Graph Embeddings: Reinterpreting Graph Convolution for Top-N Recommendation.- Meta-learning Enhanced Next POI Recommendation by Leveraging Check-ins from Auxiliary Cities.- Global-Aware External Attention Deep Model for Sequential Recommendation.- Aggregately Diversified Bundle Recommendation via Popularity Debiasing and Configuration-aware Reranking.- Diversely Regularized Matrix Factorization for Accurate and Aggregately Diversified Recommendation.- kNN-Embed: Locally Smoothed Embedding Mixtures For Multi-interest Candidate Retrieval.- Staying or Leaving: A Knowledge-Enhanced User Simulator for Reinforcement Learning Based Short Video Recommendation.- RLMixer: A Reinforcement Learning Approach For Integrated Ranking With Contrastive User Preference Modeling.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 436 pp. Englisch. Seller Inventory # 9783031333798
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Advances in Knowledge Discovery and Data Mining: 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, Osaka, Japan, May . (Lecture Notes in Artificial Intelligence)
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