Titlebook: Knowledge Science, Engineering and Management; 15th International C Gerard Memmi,Baijian Yang,Meikang Qiu Conference proceedings 2022 The E

moribund

Multi-view Heterogeneous Network Embeddinggence and development of network embedding, it has become an effective tool for processing networked data. However, most existing network embedding methods are designed for single-view networks, which have certain limitations in describing and characterizing the network semantics. Therefore, it moti

飞镖

占线

Unsupervised Person Re-ID via Loose-Tight Alternate Clustering aims to match the surveillance images containing the same person. However, the performance of these methods is usually very sensitive to the change of the hyper-parameters in the clustering methods, such as the maximum distance of the neighbors and the number of clusters, which determine the qualit

弹药

Sparse Dense Transformer Network for Video Action Recognitionion to the video’s local features and ignores global information because of the limitation of Convolution kernels. Transformer based on attention mechanism is adopted to capture global information, which is inferior to CNNs in extracting local features. More features can improve video representation

排斥

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Open Relation Extraction via Query-Based Span Predictionhe previous methods either depend on external NLP tools (e.g., PoS-taggers) and language-specific relation formations, or suffer from inherent problems in sequence representations, thus leading to unsatisfactory extraction in diverse languages and domains. To address the above problems, we propose a

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Relational Triple Extraction with Relation-Attentive Contextual Semantic Representationsgether. These models intend to extract entities and predict relations simultaneously. However, they typically focus on entity pairs representations or relation representations, which ignores the contextual semantic. To tackle these problems, we introduce a three-stage relational triple extraction mo

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Mario Fast Learner: Fast and Efficient Solutions for Super Mario Brosticle focuses on reinforcement learning methods for Super Mario Bros (SMB) games. Previous methods could solve all available SMB single player open source levels by using reinforcement learning methods. The article summarizes that previous evaluation metrics include reward function, loss function an

FECK

Few-Shot Learning with Self-supervised Classifier for Complex Knowledge Base Question Answeringd to fetch entities and relations for final answer. Typically, meta-learning based models regard question types as standards to divide dataset for pseudo-tasks. However, question type, manually labeled in CQA data set, is indispensable as a filter in the support set retrieving phase, which raises tw

愤世嫉俗者

Data-Driven Approach for Investigation of Irradiation Hardening Behavior of RAFM Steelve materials problems is still a challenge. Defects and damage induced by neutron irradiation significantly affect the service performance of materials. (RAFM) steel is a very promising candidate for application in fusion reactor cladding. Understanding irradiation hardening effects in RAFM steel is