E-grāmata: Knowledge Science, Engineering and Management: 14th International Conference, KSEM 2021, Tokyo, Japan, August 14-16, 2021, Proceedings, Part I

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 CAEļ¼A 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.