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_aKnowledge Science, Engineering and Management _h[electronic resource] : _b16th International Conference, KSEM 2023, Guangzhou, China, August 16-18, 2023, Proceedings, Part I / _cedited by Zhi Jin, Yuncheng Jiang, Robert Andrei Buchmann, Yaxin Bi, Ana-Maria Ghiran, Wenjun Ma. |
250 | _a1st ed. 2023. | ||
264 | 1 |
_aCham : _bSpringer Nature Switzerland : _bImprint: Springer, _c2023. |
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300 |
_aXXIV, 457 p. 124 illus., 108 illus. in color. _bonline resource. |
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490 | 1 |
_aLecture Notes in Artificial Intelligence, _x2945-9141 ; _v14117 |
|
505 | 0 | _aKnowledge Science with Learning and AI -- Joint Feature Selection and Classifier Parameter Optimization: A Bio-inspired Approach -- Automatic Gaussian Bandwidth Selection for Kernel Principal Component Analysis -- Boosting LightWeight Depth Estimation Via Knowledge Distillation -- Graph Neural Network with Neighborhood Reconnection -- Critical Node Privacy Protection Based on Random Pruning of Critical Trees -- DSEAformer: Forecasting by De-stationary Autocorrelation with Edgebound -- Multitask-based Cluster Transmission for Few-Shot Text Classification -- Hyperplane Knowledge Graph Embedding with Path Neighborhoods and Mapping Properties -- RTAD-TP: Real- Time Anomaly Detection Algorithm for Univariate Time Series Data Based on Two- Parameter Estimation -- Multi-Sampling Item Response Ranking Neural Cognitive Diagnosis with Bilinear Feature Interaction -- A Sparse Matrix Optimization Method for Graph Neural Networks Training -- Dual-dimensional Refinement of Knowledge Graph Embedding Representation -- Contextual Information Augmented Few-Shot Relation Extraction -- Dynamic and Static Feature-aware Microservices Decomposition via Graph Neural Networks -- An Enhanced Fitness-distance Balance Slime Mould Algorithm and Its Application in Feature Selection -- Low Redundancy Learning for Unsupervised Multi-view Feature Selection -- Dynamic Feed-Forward LSTM -- Black-box Adversarial Attack on Graph Neural Networks Based on Node Domain Knowledge -- Role and Relationship-Aware Representation Learning for Complex Coupled Dynamic Heterogeneous Networks -- Twin Graph Attention Network with Evolution Pattern Learner for Few-Shot Temporal Knowledge Graph Completion -- Subspace Clustering with Feature Grouping for Categorical Data -- Learning Graph Neural Networks on Feature-Missing Graphs -- Dealing with Over-reliance on Background Graph for Few-shot Knowledge Graph Completion -- Kernel-based feature extraction for time series clustering -- Cluster Robust Inference for embedding-based Knowledge Graph Completion -- Community-enhanced Contrastive Siamese networks for Graph Representation Learning -- Distant Supervision Relation Extraction with Improved PCNN and Multi-level Attention -- Enhancing Adversarial Robustness via Anomaly-aware Adversarial Training -- An Improved Cross-Validated Adversarial Validation Method -- EACCNet: Enhanced Auto-Cross Correlation Network for Few-Shot Classification -- Joint Label-Structure Estimation from Multifaceted Graph Data -- Dual Channel Knowledge Graph Embedding with Ontology Guided Data Augmentation -- Multi-Dimensional Graph Rule Learner -- MixUNet: A Hybrid Retinal Vessels Segmentation Model Combining The Latest CNN and MLPs -- Robust Few-shot Graph Anomaly Detection via Graph Coarsening -- An Evaluation Metric for Prediction Stability with Imprecise Data -- ReducingThe Teacher-Student Gap Via Elastic Student. | |
520 | _aThis volume set constitutes the refereed proceedings of the 16th International Conference on Knowledge Science, Engineering and Management, KSEM 2023, which was held in Guangzhou, China, during August 16-18, 2023. The 114 full papers and 30 short papers included in this book were carefully reviewed and selected from 395 submissions. They were organized in topical sections as follows: knowledge science with learning and AI; knowledge engineering research and applications; knowledge management systems; and emerging technologies for knowledge science, engineering and management. . | ||
650 | 0 |
_aArtificial intelligence. _93407 |
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650 | 0 |
_aComputer engineering. _910164 |
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650 | 0 |
_aComputer networks . _931572 |
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650 | 0 |
_aComputers. _98172 |
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650 | 0 |
_aSocial sciences _xData processing. _983360 |
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650 | 0 |
_aComputer science. _99832 |
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650 | 1 | 4 |
_aArtificial Intelligence. _93407 |
650 | 2 | 4 |
_aComputer Engineering and Networks. _9123058 |
650 | 2 | 4 |
_aComputing Milieux. _955441 |
650 | 2 | 4 |
_aComputer Application in Social and Behavioral Sciences. _931815 |
650 | 2 | 4 |
_aComputer Science. _99832 |
700 | 1 |
_aJin, Zhi. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _9123059 |
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700 | 1 |
_aJiang, Yuncheng. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _9123060 |
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700 | 1 |
_aBuchmann, Robert Andrei. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _9123061 |
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700 | 1 |
_aBi, Yaxin. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _9123062 |
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700 | 1 |
_aGhiran, Ana-Maria. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _9123063 |
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700 | 1 |
_aMa, Wenjun. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _9123064 |
|
710 | 2 |
_aSpringerLink (Online service) _9123065 |
|
773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9783031402821 |
776 | 0 | 8 |
_iPrinted edition: _z9783031402845 |
830 | 0 |
_aLecture Notes in Artificial Intelligence, _x2945-9141 ; _v14117 _9123066 |
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