2021 2nd International Symposium on Computer Engineering and Intelligent Communications (ISCEIC)最新文献

Research on data desensitization and penetration of intranet and extranet based on access control 基于访问控制的内外网数据脱敏与渗透研究

2021 2nd International Symposium on Computer Engineering and Intelligent Communications (ISCEIC) Pub Date : 2021-08-01 DOI: 10.1109/ISCEIC53685.2021.00048

Dong Wang, Wenhao Xue, Lili Li, Jiangtao Li

引用次数: 2

MLResNet: An Efficient Method for Automatic Modulation Classification Based on Residual Neural Network 基于残差神经网络的调制自动分类方法MLResNet

2021 2nd International Symposium on Computer Engineering and Intelligent Communications (ISCEIC) Pub Date : 2021-08-01 DOI: 10.1109/ISCEIC53685.2021.00032

Mingqing Xue, Ming Huang, J. Yang, Ji Da Wu

引用次数: 1

A Top-N recommendation algorithm based on graph convolutional network that integrates basic user information 一种集成用户基本信息的基于图卷积网络的Top-N推荐算法

2021 2nd International Symposium on Computer Engineering and Intelligent Communications (ISCEIC) Pub Date : 2021-08-01 DOI: 10.1109/ISCEIC53685.2021.00055

Jinling Xu, Ting Wang, Chenjie Su, Zengping Zhang, Xiaodong Cheng

{"title":"A Top-N recommendation algorithm based on graph convolutional network that integrates basic user information","authors":"Jinling Xu, Ting Wang, Chenjie Su, Zengping Zhang, Xiaodong Cheng","doi":"10.1109/ISCEIC53685.2021.00055","DOIUrl":"https://doi.org/10.1109/ISCEIC53685.2021.00055","url":null,"abstract":"In order to solve the problem of data sparseness and cold start of the collaborative filtering model, many methods have been proposed, but most of them ignore the user attribute similarity and the user preference. The accuracy of recommendation needs to be improved. Most of researches stay in simple linear modeling of the relationship between users and items, and does not consider the influence of auxiliary information on the recommendation algorithm. In our real life, users preferences are affected by age, gender, and personality. Environment, social circle, etc.In this work, we design a Top-N recommendation algorithm LNGCF-B (light neural graph collaborative filtering with user basic information). Firstly, different from traditional graph convolutional collaborative filtering algorithm, the simplified version is more explanatory, the training time is shortened. Secondly, this algorithm considers the attributes of the user, experiments show that LNGCF-B is better than the baseline algorithm. In our social life, there are many different types of networks, under different network models, the performance of the recommendation algorithm is also different. However, there are few researches on the performance of recommendation algorithms in different scenarios. We use LNGCF-B on two data sets belonging to different network models. The results show that the list recommended by the algorithm on the Movielens 100K data set belonging to the scale-free network has a higher degree of relevance, and the Facebook friend relationship data set belonging to the small world network has a higher recall rate.","PeriodicalId":342968,"journal":{"name":"2021 2nd International Symposium on Computer Engineering and Intelligent Communications (ISCEIC)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126727062","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Painting Image Retrieval Method Based on Color and Texture Features 基于颜色和纹理特征的绘画图像检索方法

2021 2nd International Symposium on Computer Engineering and Intelligent Communications (ISCEIC) Pub Date : 2021-08-01 DOI: 10.1109/ISCEIC53685.2021.00073

Jiangqi Hu, G. Cui, Xiukai Ruan, Yishan Jiang

引用次数: 0

MM-FPN: Multi-path and Multi-scale Feature Pyramid Network for Object Detection MM-FPN:用于目标检测的多路径多尺度特征金字塔网络

2021 2nd International Symposium on Computer Engineering and Intelligent Communications (ISCEIC) Pub Date : 2021-08-01 DOI: 10.1109/ISCEIC53685.2021.00072

Sheng Dong, Jiaxin Zhang, Zehui Qu

引用次数: 0

Image Segmentation Algorithm Based on Jump Feature Fusion and Rich Features 基于跳跃特征融合和富特征的图像分割算法

2021 2nd International Symposium on Computer Engineering and Intelligent Communications (ISCEIC) Pub Date : 2021-08-01 DOI: 10.1109/ISCEIC53685.2021.00053

Yanjun Wei, Tonghe Ding, Tianping Li, Kaili Feng

引用次数: 0

Research on posts analysis based on data process automation 基于数据流程自动化的岗位分析研究

2021 2nd International Symposium on Computer Engineering and Intelligent Communications (ISCEIC) Pub Date : 2021-08-01 DOI: 10.1109/ISCEIC53685.2021.00039

Taizhi Lv, Jun Zhang, Chenyong He

引用次数: 2

Short Term Wind Speed Forecasting Based on Feature Extraction by CNN and MLP 基于CNN和MLP特征提取的短期风速预报

2021 2nd International Symposium on Computer Engineering and Intelligent Communications (ISCEIC) Pub Date : 2021-08-01 DOI: 10.1109/ISCEIC53685.2021.00047

Hui Wang, Jilong Wang

{"title":"Short Term Wind Speed Forecasting Based on Feature Extraction by CNN and MLP","authors":"Hui Wang, Jilong Wang","doi":"10.1109/ISCEIC53685.2021.00047","DOIUrl":"https://doi.org/10.1109/ISCEIC53685.2021.00047","url":null,"abstract":"At present, most of the short-term wind speed forecasting researches directly use the original data as the input or break them down, and take the decomposed series as the input for forecasting model. There is a lack of feature analysis of the original data and the decomposed series. In this paper, from the perspective of feature analysis of wind speed, Ensemble Empirical Mode Decomposition (EEMD) and Convolutional Neural Networks (CNN) are used to decompose the sequence and extract features, and Multilayer Perceptron (MLP) is used to predict the wind speed. Firstly, EEMD is used to decompose the wind speed into a series of subsequences; Secondly, CNN is used to extract the features of each decomposition layer, and the input variables of each decomposition layer are constructed; Finally, MLP is used to predict each decomposition layer; At the same time, Adam is used to optimize the parameters of CNN and MLP. The results of case study and comparison show that EEMD-CNN-MLP-Adam has high prediction and good generalization, which can provide reference for wind speed prediction in different regions and periods.","PeriodicalId":342968,"journal":{"name":"2021 2nd International Symposium on Computer Engineering and Intelligent Communications (ISCEIC)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134477035","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Design of a Cloud-based Paging Intelligent Classroom Recording and Broadcasting System 基于云的寻呼式智能教室录播系统设计

2021 2nd International Symposium on Computer Engineering and Intelligent Communications (ISCEIC) Pub Date : 2021-08-01 DOI: 10.1109/ISCEIC53685.2021.00076

Cuilian Liu, Caijie Lin, Ruihong Lin, Yibo Li, Zexin Fan

引用次数: 0

New energy charging pile planning in residential area based on improved genetic algorithm 基于改进遗传算法的小区新能源充电桩规划

2021 2nd International Symposium on Computer Engineering and Intelligent Communications (ISCEIC) Pub Date : 2021-08-01 DOI: 10.1109/ISCEIC53685.2021.00011

Liu Yang

引用次数: 0