CONVOLUTION

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How graph convolutions amplify popularity bias for recommendation?
《Frontiers of Computer Science》2024年第5期121-132,共12页Jiajia CHEN Jiancan WU Jiawei CHEN Xin XIN Yong LI Xiangnan HE 
This work was supported by the National Key R&D Program of China(2021ZD0111802);the National Natural Science Foundation of China(Grant No.19A2079);the CCCD Key Lab of Ministry of Culture and Tourism.
Graphconvolutional networks(GCNs)have become prevalent in recommender system(RS)due to their superiority in modeling collaborative patterns.Although improving the overall accuracy,GCNs unfortunately amplify popularity...
关键词：RECOMMENDATION graph convolution networks popularity bias 
Aspect-level sentiment analysis based on semantic heterogeneous graph convolutional network被引量：1
《Frontiers of Computer Science》2023年第6期87-99,共13页Yufei ZENG Zhixin LI Zhenbin CHEN Huifang MA 
supported by the National Natural Science Foundation of China(Grant Nos.62276073,61966004);Guangxi Natural Science Foundation(No.2019GXNSFDA245018);Innovation Project of Guangxi Graduate Education(No.YCSW2022155);Guangxi“Bagui Scholar”Teams for Innovation and Research Project;Guangxi Collaborative Innovation Center of Multi-source Information Integration and Intelligent Processing.
The deep learning methods based on syntactic dependency tree have achieved great success on Aspect-based Sentiment Analysis(ABSA).However,the accuracy of the dependency parser cannot be determined,which may keep aspec...
关键词：heterogeneous graph convolution network multi-head attention network aspect-based sentiment analysis deep learning affective knowledge 
Dynamic depth-width optimization for capsule graph convolutional network
《Frontiers of Computer Science》2023年第6期159-161,共3页Shangwei WU Yingtong XIONG Chuliang WENG 
supported by the National Natural Science Foundation of China(Grant Nos.62141214 and 62272171).
1 Introduction Encouraged by the success of Convolutional Neural Networks(CNNs),many studies[1],known as Graph Convolutional Networks(GCNs),borrowed the idea of convolution and redefined it for graph data.In graph-lev...
关键词：CONVOLUTION REPRESENTATION mutual 
Dynamic traveling time forecasting based on spatial-temporal graph convolutional networks
《Frontiers of Computer Science》2023年第6期179-181,共3页Fangshu CHEN Yufei ZHANG Lu CHEN Xiankai MENG Yanqiang QI Jiahui WANG 
supported by the National Natural Science Foundation of China(NSFC)(Grant No.62002216);the Shanghai Sailing Program(No.20YF1414400);the Collaborative Innovation Platform of Electronic Information Master of Shanghai Polytechnic University(SSPU)(No.A10GY21F015);the Research Projects of Shanghai Polytechnic University(Nos.EGD22QD03,EGD23DS05);the Key Disciplines of Computer Science and Technology of SSPU and the Construction of Electronic Information Master Degree of SSPU.
1 Introduction Traveling time forecasting,the core component in GPS navigation systems and taxi-hailing apps,has attracted widespread attention.Existing research mostly focuses on independent points like traffic flow ...
关键词：forecasting TRAVELING CONVOLUTION 
Graph convolution machine for context-aware recommender system被引量：5
《Frontiers of Computer Science》2022年第6期81-92,共12页Jiancan WU Xiangnan HE Xiang WANG Qifan WANG Weijian CHEN Jianxun LIAN Xing XIE 
supported by the National Key Research and Development Program of China (2020AAA0106000);the National Natural Science Foundation of China (Grant Nos.61972372,U19A2079,62121002).
The latest advance in recommendation shows that better user and item representations can be learned via performing graph convolutions on the user-item interaction graph.However,such finding is mostly restricted to the...
关键词：context-aware recommender systems graph convolution 
Instance-sequence reasoning for video question answering被引量：1
《Frontiers of Computer Science》2022年第6期93-101,共9页Rui LIU Yahong HAN 
supported by the National Natural Science Foundation of China (Grant Nos.61876130,61932009).
Video question answering(Video QA)involves a thorough understanding of video content and question language,as well as the grounding of the textual semantic to the visual content of videos.Thus,to answer the questions ...
关键词：video question answering instance grounding graph causal convolution 
Accelerating temporal action proposal generation via high performance computing
《Frontiers of Computer Science》2022年第4期59-68,共10页Tian Wang Shiye Lei Youyou Jiang Choi Chang Hichem Snoussi Guangcun Shan Yao Fu 
supported by the National Key Research and Development Program of China(2016YFE0204200);the National Natural Science Foundation of China(Grant Nos,61972016,62032016);Bejing Natural Science Foundation(L191007);the Fundamental Research Funds for the Central Universities(YWF-21-BJ-J-313 and YWF-20-BJ-J-612);Open Research Fund of Digital Fujian Environment Monitoring Internet of Things Laboratory Foundation(202004).
Temporal action proposal generation aims to output the starting and ending times of each potential action for long videos and often suffers from high computation cost.To address the issue,we propose a new temporal con...
关键词：temporal convolution temporal action proposal generation deep learning 
Local feature aggregation algorithm based on graph convolutional network被引量：2
《Frontiers of Computer Science》2022年第3期203-205,共3页Hao WANG Liyan DONG Minghui SUN 
the National Natural Science Foundation of China(Grant Nos.61272209,61872164);in part by the Program of Science and Technology Development Plan of Jilin Province of China(20190302032GX);in part by the Fundamental Research Funds for the Central Universities(Jilin University).
1Introduction and main contributions In the field of social networks and knowledge graphs,semi-supervised learning models based on graph convolutional networks have achieved great success in node classification[1],ind...
关键词：CONVOLUTION AGGREGATION SEMI 
Deep model-based feature extraction for predicting protein subcellular localizations from bio-images
《Frontiers of Computer Science》2017年第2期243-252,共10页Wei SHAO Yi DING Hong-Bin SHEN Daoqiang ZHANG 
This work was supported in part by the National Nat- ural Science Foundation of China （Grant Nos. 61422204, 61473149 and 61671288）, Jiangsu Natural Science Foundation for Distinguished Young Scholar （BK20130034）, and Science and Technology Commission of Shang- hai Municipality （16JC1404300）.
Protein subcellular localization prediction is im- portant for studying the function of proteins. Recently, as significant progress has been witnessed in the field of mi- croscopic imaging, automatically determining t...
关键词：partial parameter transfer subcellular location classification feature extraction deep model convolution neural network 
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