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.