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200911 ||| eng |
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|a 9783030551308
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| 100 |
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|a Li, Gang
|e [editor]
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| 245 |
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|a Knowledge Science, Engineering and Management
|h Elektronische Ressource
|b 13th International Conference, KSEM 2020, Hangzhou, China, August 28–30, 2020, Proceedings, Part I
|c edited by Gang Li, Heng Tao Shen, Ye Yuan, Xiaoyang Wang, Huawen Liu, Xiang Zhao
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| 250 |
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|a 1st ed. 2020
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| 260 |
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|a Cham
|b Springer International Publishing
|c 2020, 2020
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| 300 |
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|a XXVI, 510 p. 202 illus., 116 illus. in color
|b online resource
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|a Fast Backward Iterative Laplacian Score for Unsupervised Feature Selection -- Improving Low-Resource Chinese Event Detection with Multi-Task Learning -- Feature Selection Using Sparse Twin Support Vector Machine with correntropy-induces loss -- Customized Decision Tree for Fat Multi-resolution Chart Patterns Classification -- Predicting user influence in the propagation of toxic information -- Extracting Distinctive Shapelets with Random Selection for Early Classification -- Butterfly-Based Higher-Order Clustering on Bipartite Networks -- Learning Dynamic Pricing Rules for Flight Tickets
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| 505 |
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|a A Hybrid Model with Pre-trained Entity-Aware Transformer for Relation Extraction -- NovEA: A Novel Model of Entity Alignment Using Attribute Triples and Relation Triples -- A Robust Representation with Pre-Trained Start and End Characters Vectors for Noisy Word Recognition -- Intention Multiple-representation Model for Logistics Intelligent Customer Service -- Identifying Loners from Their Project Collaboration Records – A Graph-based Approach -- Node Embedding over Attributed Bipartite Graphs -- FastLogSim: A quick log pattern parser scheme based on text similarity -- Knowledge Management for Education -- Robotic Pushing and Grasping Knowledge Learning via Attention Deep Q-Learning Network -- A Dynamic Answering Path based Fusion Model for KGQA -- Improving Deep Item-based Collaborative Filtering with Bayesian Personalized Ranking for MOOC Course Recommendation -- Online Programming Education Modeling and Knowledge Tracing --
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|a Knowledge Graph -- Event-centric Tourism Knowledge Graph — A Case Study of Hainan -- Extracting Short Entity Descriptions for Open-World Extension to Knowledge Graph Completion Models -- Graph Embedding Based on Characteristic of Rooted Subgraph Structure -- Knowledge Graphs Meet Geometry for Semi-supervised Monocular Depth Estimation -- Topological Graph Representation Learning on Property Graph -- Measuring Triplet Trustworthiness in Knowledge Graphs via Expanded Relation Detection -- A Contextualized Entity Representation for Knowledge Graph Completion -- A Dual Fusion Model for Attributed Network Embedding -- Attention-based Knowledge Tracing with Heterogeneous Information Network Embedding -- Knowledge Representation -- Detecting Statistically Significant Events in Large Heterogeneous Attribute Graphs via Densest Subgraphs -- Edge Features Enhanced Graph Attention Network for Relation Extraction -- MMEA: Entity Alignment for Multi-Modal Knowledge Graph --
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|a Enhancing Pre-Trained Language Models by Self-Supervised Learning for Story Cloze Test -- MOOCRec: An Attention Meta-path Based Model for Top-K Recommendation in MOOC -- Knowledge-based Systems -- PVFNet: Point-view fusion network for 3D shape recognition -- HEAM: Heterogeneous Network Embedding with Automatic Meta-path Construction -- A Graph Attentive Network Model for P2P Lending Fraud Detection -- An Empirical Study on Recent Graph Database Systems -- Bibliometric Analysis of Twitter Knowledge management publications related to Health Promotion -- Automatic cerebral artery system labeling using registration and key points tracking -- Page-level handwritten word spotting via discriminative feature learning -- NADSR: A Network Anomaly Detection Scheme based on Representation -- A Knowledge-based Scheduling Method for Multi-Satellite Range System -- IM-Net: Semantic Segmentation Algorithm for Medical Images Based on Mutual Information Maximization -- Data Processing and Mining --
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| 653 |
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|a Computer Application in Social and Behavioral Sciences
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| 653 |
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|a Artificial Intelligence
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| 653 |
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|a Social sciences / Data processing
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| 653 |
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|a Database Management
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| 653 |
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|a Data mining
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| 653 |
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|a Application software
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| 653 |
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|a Computer Application in Administrative Data Processing
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| 653 |
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|a Artificial intelligence
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| 653 |
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|a Data Mining and Knowledge Discovery
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| 653 |
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|a Computer and Information Systems Applications
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| 653 |
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|a Information technology / Management
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| 653 |
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|a Database management
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| 700 |
1 |
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|a Shen, Heng Tao
|e [editor]
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| 700 |
1 |
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|a Yuan, Ye
|e [editor]
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| 700 |
1 |
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|a Wang, Xiaoyang
|e [editor]
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b Springer
|a Springer eBooks 2005-
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| 490 |
0 |
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|a Lecture Notes in Artificial Intelligence
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| 028 |
5 |
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|a 10.1007/978-3-030-55130-8
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| 856 |
4 |
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|u https://doi.org/10.1007/978-3-030-55130-8?nosfx=y
|x Verlag
|3 Volltext
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| 082 |
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|a 006.3
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| 520 |
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|a This two-volume set of LNAI 12274 and LNAI 12275 constitutes the refereed proceedings of the 13th International Conference on Knowledge Science, Engineering and Management, KSEM 2020, held in Hangzhou, China, in August 2020.* The 58 revised full papers and 27 short papers were carefully reviewed and selected from 291 submissions. The papers of the first volume are organized in the following topical sections: knowledge graph; knowledge representation; knowledge management for education; knowledge-based systems; and data processing and mining. The papers of the second volume are organized in the following topical sections: machine learning; recommendation algorithms and systems; social knowledge analysis and management; text mining and document analysis; and deep learning. *The conference was held virtually due to the COVID-19 pandemic
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