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Knowledge Science, Engineering and Management = 14th International Conference, KSEM 2021, Tokyo, Japan, August 14–16, 2021, Proceedings, Part I /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Knowledge Science, Engineering and Management/ edited by Han Qiu, Cheng Zhang, Zongming Fei, Meikang Qiu, Sun-Yuan Kung.
其他題名:	14th International Conference, KSEM 2021, Tokyo, Japan, August 14–16, 2021, Proceedings, Part I /
其他作者:	Kung, Sun-Yuan.
面頁冊數:	XXVII, 710 p. 220 illus., 189 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Algorithm Analysis and Problem Complexity. -
電子資源:	https://doi.org/10.1007/978-3-030-82136-4
ISBN:	9783030821364

Knowledge Science, Engineering and Management = 14th International Conference, KSEM 2021, Tokyo, Japan, August 14–16, 2021, Proceedings, Part I /
Knowledge Science, Engineering and Management14th International Conference, KSEM 2021, Tokyo, Japan, August 14–16, 2021, Proceedings, Part I /[electronic resource] :edited by Han Qiu, Cheng Zhang, Zongming Fei, Meikang Qiu, Sun-Yuan Kung. - 1st ed. 2021. - XXVII, 710 p. 220 illus., 189 illus. in color.online resource. - Lecture Notes in Artificial Intelligence ;12815. - Lecture Notes in Artificial Intelligence ;9285.

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 on User’s 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.

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.

ISBN: 9783030821364

Standard No.: 10.1007/978-3-030-82136-4doiSubjects--Topical Terms:

593923
Algorithm Analysis and Problem Complexity.

LC Class. No.: Q334-342

Dewey Class. No.: 006.3

Knowledge Science, Engineering and Management = 14th International Conference, KSEM 2021, Tokyo, Japan, August 14–16, 2021, Proceedings, Part I /
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