Knowledge Science, Engineering and Management

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 onUser'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.