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Knowledge Science, Engineering and Management: 14th International Conference, KSEM 2021, Tokyo, Japan, August 1416, 2021, Proceedings, Part I 1st ed. 2021 [Pehme köide]

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  • Formaat: Paperback / softback, 710 pages, kõrgus x laius: 235x155 mm, kaal: 1116 g, 189 Illustrations, color; 31 Illustrations, black and white; XXVII, 710 p. 220 illus., 189 illus. in color., 1 Paperback / softback
  • Sari: Lecture Notes in Computer Science 12815
  • Ilmumisaeg: 21-Jul-2021
  • Kirjastus: Springer Nature Switzerland AG
  • ISBN-10: 3030821358
  • ISBN-13: 9783030821357
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  • Formaat: Paperback / softback, 710 pages, kõrgus x laius: 235x155 mm, kaal: 1116 g, 189 Illustrations, color; 31 Illustrations, black and white; XXVII, 710 p. 220 illus., 189 illus. in color., 1 Paperback / softback
  • Sari: Lecture Notes in Computer Science 12815
  • Ilmumisaeg: 21-Jul-2021
  • Kirjastus: Springer Nature Switzerland AG
  • ISBN-10: 3030821358
  • ISBN-13: 9783030821357
This three-volume set constitutes the refereed proceedings of the 14th International Conference on Knowledge Science, Engineering and Management, KSEM 2021, held in Tokyo, Japan, in August 2021.

The 164 revised full papers were carefully reviewed and selected from 492 submissions. The contributions are organized in the following topical sections: knowledge science with learning and AI; knowledge engineering research and applications; knowledge management with optimization and security.

Knowledge Science with Learning and AI (KSLA).- Research on Innovation
Trends of AI Applied to Medical Instruments Using Informetrics Based on
Multi-Sourse Information.- Extracting Prerequisite Relations among Wikipedia
Concepts using the Clickstream Data.- Clustering Massive-categories and
Complex Documents via Graph Convolutional Network.- Structure-enhanced Graph
Representation Learning for Link Prediction in Signed Networks.- A
Property-based Method for Acquiring Commonsense Knowledge.- Multi-hop
Learning promote Cooperation in Multi-agent Systems.- FedPS: Model
Aggregation with Pseudo Samples.- Dense Incremental Extreme Learning Machine
with Accelerating.- Amount and Proportional Integral Differential.-
Knowledge-based Diverse Feature Transformation For Few-shot Relation
Classification.- Community Detection In Dynamic Networks: A Novel Deep
Learning Method.- Additive Noise Model Structure Learning Based on Rank
Statistics.- A MOOCs Recommender System Based onUsers Knowledge
Background.- TEBC-Net: An effective relation extraction approach for simple
question answering over knowledge graphs.- Representing Knowledge Graphs with
Gaussian Mixture Embedding.- A Semi-supervised Multi-objective Evolutionary
Algorithm for Multi-layer Network Community Detection.- Named Entity
Recognition Based on Reinforcement Learning and Adversarial Training.-
Improved Partitioning Graph Embedding Framework for Small Cluster.- A
Framework of Data Fusion through Spatio-temporal Knowledge Graph.- SEGAR:
Knowledge Graph Augmented Session-based Recommendation.- Symbiosis: A Novel
Framework for Integrating Hierarchies from Knowledge Graph into
Recommendation System.- An Ensemble Fuzziness-based Online Sequential
Learning Approach and Its Application.- GASKT: A Graph-based Attentive
Knowledge-Search Model for Knowledge Tracing.- Fragile Neural Network
Watermarking with Trigger Image Set.- Introducing Graph Neural Networks for
Few-Shot Relation Prediction in Knowledge Graph Completion Task.- A Research
Study on Running Machine Learning Algorithms on Big Data with
Spark.- Attentional Neural Factorization Machines for Knowledge Tracing.-
Node-Image CAEï¼A Novel Embedding Method via Convolutional Auto-Encoder and
High-Order Proximities.- EN-DIVINE: An Enhanced Generative Adversarial
Imitation Learning Framework for Knowledge Graph Reasoning.- Knowledge
Distillation via Channel Correlation Structure.- Feature Interaction
Convolutional Network for Knowledge Graph Embedding.- Towards a Modular
Ontology for Cloud Consumer Review Mining.- Identification of Critical Nodes
in Urban Transportation Network through Network Topology and Server Routes.-
Graph Ensemble Networks for Semi-Supervised Embedding Learning.- Rethinking
the Information inside Documents for Sentiment Classification.- Dependency
Parsing Representation Learning for Open Information Extraction.-
Hierarchical Policy Network with Multi-Agent for Knowledge Graph Reasoning
Based on Reinforcement Learning.- Inducing Bilingual Word Representations for
Non-Isomorphic Spaces by an Unsupervised Way.- A Deep Learning Model Based on
Neural Bag-of-words Attention for Sentiment Analysis.- Graph Attention
Mechanism with Cardinality Preservation for Knowledge Graph Completion.-
Event Relation Reasoning Based on Event Knowledge Graph.- PEN4Rec: Preference
Evolution Networks for Session-based Recommendation.- HyperspherE: An
Embedding Method for Knowledge Graph Completion Based on Hypersphere.- TroBo:
A Novel Deep Transfer Model for Enhancing Cross-project Bug Localization.- A
Neural Language Understanding for Dialogue State Tracking.- Spirit
Distillation: A Model Compression Method with Multi-domain Knowledge
Transfer.- Knowledge Tracing with Exercise-Enhanced Key-Value Memory
Networks.- Entity Alignment between Knowledge Graphs Using Entity Type
Matching.- Text-Aware Recommendation Model Based on Multi-Attention Neural
Network.- Chinese Named Entity Recognition Based on Gated Graph Neural
Network.- Learning a Similarity Metric Discriminatively with Application to
Ancient Character Recognition.- Incorporating Global Context into Multi-task
Learning for Session-based Recommendation.- Exploring Sequential and
Collaborative Contexts for Next Point-of-Interest Recommendation.- Predicting
User Preferences via Heterogeneous Information Network and Metric
Learning.- An IoT Ontology Class Recommendation Method Based on Knowledge
Graph.- Ride-Sharing Matching of Commuting Private Car using Reinforcement
Learning.- Optimization of Remote Desktop with CNN Based Image
Compression Model.