LEADER 06365nam 22007575 450 001 996546853603316 005 20230810133506.0 010 $a3-031-40283-9 024 7 $a10.1007/978-3-031-40283-8 035 $a(CKB)27965606200041 035 $a(DE-He213)978-3-031-40283-8 035 $a(PPN)272260061 035 $a(MiAaPQ)EBC31214934 035 $a(Au-PeEL)EBL31214934 035 $a(EXLCZ)9927965606200041 100 $a20230803d2023 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aKnowledge Science, Engineering and Management$b[electronic resource] $e16th International Conference, KSEM 2023, Guangzhou, China, August 16?18, 2023, Proceedings, Part I /$fedited by Zhi Jin, Yuncheng Jiang, Robert Andrei Buchmann, Yaxin Bi, Ana-Maria Ghiran, Wenjun Ma 205 $a1st ed. 2023. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2023. 215 $a1 online resource (XXIV, 457 p. 124 illus., 108 illus. in color.) 225 1 $aLecture Notes in Artificial Intelligence,$x2945-9141 ;$v14117 311 $a3-031-40282-0 327 $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 -- Reducing The Teacher-Student Gap Via Elastic Student. 330 $aThis volume set constitutes the refereed proceedings of the 16th International Conference on Knowledge Science, Engineering and Management, KSEM 2023, which was held in Guangzhou, China, during August 16?18, 2023. The 114 full papers and 30 short papers included in this book were carefully reviewed and selected from 395 submissions. They were organized in topical sections as follows: knowledge science with learning and AI; knowledge engineering research and applications; knowledge management systems; and emerging technologies for knowledge science, engineering and management. . 410 0$aLecture Notes in Artificial Intelligence,$x2945-9141 ;$v14117 606 $aArtificial intelligence 606 $aComputer engineering 606 $aComputer networks 606 $aComputers 606 $aSocial sciences$xData processing 606 $aComputer science 606 $aArtificial Intelligence 606 $aComputer Engineering and Networks 606 $aComputing Milieux 606 $aComputer Application in Social and Behavioral Sciences 606 $aComputer Science 615 0$aArtificial intelligence. 615 0$aComputer engineering. 615 0$aComputer networks. 615 0$aComputers. 615 0$aSocial sciences$xData processing. 615 0$aComputer science. 615 14$aArtificial Intelligence. 615 24$aComputer Engineering and Networks. 615 24$aComputing Milieux. 615 24$aComputer Application in Social and Behavioral Sciences. 615 24$aComputer Science. 676 $a006.3 702 $aJin$b Zhi$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aJiang$b Yuncheng$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aBuchmann$b Robert Andrei$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aBi$b Yaxin$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aGhiran$b Ana-Maria$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aMa$b Wenjun$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996546853603316 996 $aKnowledge Science, Engineering and Management$9772454 997 $aUNISA