发布求助
文献互助 智能选刊 最新文献

2020 2nd International Conference on Information Technology and Computer Application (ITCA)最新文献

筛选
英文 中文
Sales Forecasting Based on CatBoost 基于CatBoost的销售预测
2020 2nd International Conference on Information Technology and Computer Application (ITCA) Pub Date : 2020-12-01 DOI: 10.1109/ITCA52113.2020.00138
Jingyi Ding, Ziqing Chen, Li Xiaolong, Baoxin Lai
{"title":"Sales Forecasting Based on CatBoost","authors":"Jingyi Ding, Ziqing Chen, Li Xiaolong, Baoxin Lai","doi":"10.1109/ITCA52113.2020.00138","DOIUrl":"https://doi.org/10.1109/ITCA52113.2020.00138","url":null,"abstract":"Sales forecasting is a vital technology nowadays in the retail industry. With the help of advanced machine learning and deep learning algorithms, business owners can accurately predict the sales of thousands of products and make optimum decisions based on them. In this paper, we proposed a sales forecasting system based on CatBoosting. The algorithm is trained on the Walmart sales dataset, by far the largest dataset in this field. We performed effective feature engineering to boost prediction accuracy and speed. In the experiments, our model outperforms traditional machine learning methods like Linear Regression and SVM, reaching an RMSE of 0. 605. Our method doesn't need as much finetuning as other methods thus improving its generalization ability on other custom datasets, expanding its potential use.","PeriodicalId":103309,"journal":{"name":"2020 2nd International Conference on Information Technology and Computer Application (ITCA)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133351280","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: 5
Similarity search of graph database based on Fuzzy Logic Support vector machine (PSO-SVM) algorithm and computer application 基于模糊逻辑支持向量机(PSO-SVM)算法及计算机应用的图数据库相似度搜索
2020 2nd International Conference on Information Technology and Computer Application (ITCA) Pub Date : 2020-12-01 DOI: 10.1109/itca52113.2020.00027
Tao Yu, Feng He
{"title":"Similarity search of graph database based on Fuzzy Logic Support vector machine (PSO-SVM) algorithm and computer application","authors":"Tao Yu, Feng He","doi":"10.1109/itca52113.2020.00027","DOIUrl":"https://doi.org/10.1109/itca52113.2020.00027","url":null,"abstract":"Support vector machine (SVM) has excellent learning performance, has become a popular research method in the field of machine learning, and has been successfully applied in many fields. In recent years, more and more modeling methods have been put forward by relevant scholars to solve problems such as classification identification, risk prediction, and effectiveness evaluation. This article briefly introduces the support vector machine (SVM), and expounds the algorithm of support vector machine in graph database similarity search and computer application for readers’ reference.","PeriodicalId":103309,"journal":{"name":"2020 2nd International Conference on Information Technology and Computer Application (ITCA)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126002090","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
An empirical analysis of the key factors affecting the inter school sharing of regional digital teaching resources 影响区域数字化教学资源校际共享关键因素的实证分析
2020 2nd International Conference on Information Technology and Computer Application (ITCA) Pub Date : 2020-12-01 DOI: 10.1109/ITCA52113.2020.00153
Wei Wang
{"title":"An empirical analysis of the key factors affecting the inter school sharing of regional digital teaching resources","authors":"Wei Wang","doi":"10.1109/ITCA52113.2020.00153","DOIUrl":"https://doi.org/10.1109/ITCA52113.2020.00153","url":null,"abstract":"The regional digital teaching resources sharing among schools is becoming more and more popular, but restricted by some factors. It is of great practical significance to find out the key influencing factors to guide the regional digital teaching resources sharing among schools. In this paper, Suzhou International Education Park is taken as the empirical research object of the key influencing factors of regional digital teaching resources sharing between schools. Spss19.0 statistical software is used to process and analyze the collected information, find out the key influencing factors, and then carry out logistic regression analysis, finally forming the research conclusion","PeriodicalId":103309,"journal":{"name":"2020 2nd International Conference on Information Technology and Computer Application (ITCA)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130255672","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: 0
Research on the application of Minnan architectural pattern elements in ceramics cultural creation under the background of big data 大数据背景下闽南建筑图案元素在陶瓷文化创作中的应用研究
2020 2nd International Conference on Information Technology and Computer Application (ITCA) Pub Date : 2020-12-01 DOI: 10.1109/ITCA52113.2020.00093
Xiaoping Zhou, Yanmin Liu, Liang Xiaobo, Peng Zixuan, Chen Zhihong
{"title":"Research on the application of Minnan architectural pattern elements in ceramics cultural creation under the background of big data","authors":"Xiaoping Zhou, Yanmin Liu, Liang Xiaobo, Peng Zixuan, Chen Zhihong","doi":"10.1109/ITCA52113.2020.00093","DOIUrl":"https://doi.org/10.1109/ITCA52113.2020.00093","url":null,"abstract":"The architectural pattern of southern Fujian is an important expression carrier of southern Fujian culture. It embodies the traditional aesthetic concepts and feelings of the Chinese nation. It is widely used in all aspects of Chinese society, and the use of ceramic decoration is particularly eye-catching. The shape, pattern, color and other artistic characteristics of the architectural lines in southern Fujian reflect a very valuable aesthetic orientation, which is worth learning from and recreating. In different fields, the effective combination of Minnan architectural pattern elements and modern ceramic craftsmanship presents a new artistic style, which fully reflects its aesthetic value. Therefore, in the technology of big data analysis, this article analyzes the architectural style of southern Fujian, and interprets how the elements of southern Fujian architectural textures are cited in modern ceramics, and analyzes how the architectural patterns of southern Fujian can improve the development of ceramic culture and creativity. This paper shows the charm of southern Fujian architecture and promote the innovation and inheritance of southern Fujian culture.","PeriodicalId":103309,"journal":{"name":"2020 2nd International Conference on Information Technology and Computer Application (ITCA)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129300313","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: 0
Multi dimensional data distribution monitoring based on OLAP 基于OLAP的多维数据分布监控
2020 2nd International Conference on Information Technology and Computer Application (ITCA) Pub Date : 2020-12-01 DOI: 10.1109/ITCA52113.2020.00070
Yifan Mao, Shasha Huang, Shuo Cui, Haifeng Wang, Junyan Zhang, Wenhao Ding
{"title":"Multi dimensional data distribution monitoring based on OLAP","authors":"Yifan Mao, Shasha Huang, Shuo Cui, Haifeng Wang, Junyan Zhang, Wenhao Ding","doi":"10.1109/ITCA52113.2020.00070","DOIUrl":"https://doi.org/10.1109/ITCA52113.2020.00070","url":null,"abstract":"With the rapid development of the Internet, society is gradually entering the information age, and various data in enterprises have become the most important strategic core resources of all enterprises. The operation and decision-making of enterprises all require a large amount of data analysis. Nowadays, many companies do not pay enough attention to the monitoring of data asset distribution. In addition, various internal systems such as financial management and ERP systems are relatively independent. Each system has its own data organization standard, which makes it difficult to conduct a unified management of data. This also directly leads to the one-sided and subjective problem of enterprise managers' distribution of data assets. With the construction of the data center of each enterprise, the data of each system is aggregated to the center through data integration technology. Therefore, all enterprises need to build a multi-dimensional data distribution monitoring model around data links to comprehensively monitor the status of various data distributions across the company's entire network, and improve data service capabilities and sharing capabilities as well as the company's operational capabilities. This article uses OLAP technology to construct a multi-dimensional data distribution monitoring model for the data link in the process of power enterprise data integration. This article first selects the dimensions and metrics that need to be monitored in the multidimensional data, and then constructs the conceptual model, logical model and physical model of the multidimensional data using on line analytical processing technology. Finally, an example analysis of OLAP system architecture based on B/S structure is realized. The overall data distribution of the enterprise can be grasped by analyzing the various dimensions of the data link, such as System type, location distribution, and time.","PeriodicalId":103309,"journal":{"name":"2020 2nd International Conference on Information Technology and Computer Application (ITCA)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129720602","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: 0
Application of computer image processing technology in Web Design 计算机图像处理技术在网页设计中的应用
2020 2nd International Conference on Information Technology and Computer Application (ITCA) Pub Date : 2020-12-01 DOI: 10.1109/ITCA52113.2020.00033
Yue Ma, Dan Guangrong
{"title":"Application of computer image processing technology in Web Design","authors":"Yue Ma, Dan Guangrong","doi":"10.1109/ITCA52113.2020.00033","DOIUrl":"https://doi.org/10.1109/ITCA52113.2020.00033","url":null,"abstract":"Computer image processing technology is an important part of web design, which can effectively improve the appeal and artistic sense of web page. With the development of the times, the influence of the network in people’s life is more and more big, web design has also been widely concerned by people. The application of computer image processing technology in web page design can make the web page more beautiful and efficient. With the continuous improvement of the current society’s attention to network publicity, it provides favorable conditions for the combination of art and network development. The application of computer image processing in web design can increase the artistry and attractiveness of web pages, and achieve the purpose of network publicity through the stimulation of people’s interest, which can greatly promote the development of the industry. This paper analyzes the web design image processing knowledge and computer image processing technology in the application of web design, for reference only.","PeriodicalId":103309,"journal":{"name":"2020 2nd International Conference on Information Technology and Computer Application (ITCA)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127581519","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: 13
Efficient Algorithm for Mining Probabilistic Frequent Itemsets of Uncertain Data 不确定数据概率频繁项集挖掘的高效算法
2020 2nd International Conference on Information Technology and Computer Application (ITCA) Pub Date : 2020-12-01 DOI: 10.1109/ITCA52113.2020.00017
Yuan Quan, Liu ZhiLong
{"title":"Efficient Algorithm for Mining Probabilistic Frequent Itemsets of Uncertain Data","authors":"Yuan Quan, Liu ZhiLong","doi":"10.1109/ITCA52113.2020.00017","DOIUrl":"https://doi.org/10.1109/ITCA52113.2020.00017","url":null,"abstract":"At present, uncertain data has become a hot research topic for scholars. For the current mining algorithms, there are still many shortcomings in terms of time and memory. How to improve or find efficient mining algorithms and quickly mine them Information that is more valuable to people has also become a thorny problem for researchers. At present, the existing algorithms for mining frequent itemsets of uncertain data probabilities with pattern growth have many shortcomings in terms of memory. Aiming at the problem that the existing PUFP-Growth algorithm consumes too much memory, this paper proposes a HUFP-Growth algorithm. This algorithm adds a candidate item set judgment mechanism to the original algorithm, which can judge the item set in advance Is it necessary to do linking to save a lot of memory. At the same time, it can also save the time consumed when the itemsets in the original algorithm are connected, and to a certain extent, it also saves the running time of the algorithm. Finally, the effectiveness of the method is proved through experiments.","PeriodicalId":103309,"journal":{"name":"2020 2nd International Conference on Information Technology and Computer Application (ITCA)","volume":"113 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117249867","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: 0
Research on Text to Image Based on Generative Adversarial Network 基于生成对抗网络的文本到图像的研究
2020 2nd International Conference on Information Technology and Computer Application (ITCA) Pub Date : 2020-12-01 DOI: 10.1109/ITCA52113.2020.00077
Li Xiaolin, Gao Yuwei
{"title":"Research on Text to Image Based on Generative Adversarial Network","authors":"Li Xiaolin, Gao Yuwei","doi":"10.1109/ITCA52113.2020.00077","DOIUrl":"https://doi.org/10.1109/ITCA52113.2020.00077","url":null,"abstract":"In recent years, Generative Adversarial Network (GAN) has quickly become the most popular deep generative model framework, and it is also the most popular topic in the current deep learning research field. Although the generative adversarial network has achieved remarkable results from text description to image generation, when a complex image containing multiple objects, the position of each object will be blurred and overlapped, and the edges of the generated image will be blurred and local textures will be unclear. Usually given text description can generate the corresponding rough image, but there are still some problems in the image details. In order to solve the above problems, on the basis of Stack GAN, a scene graph-based stacked generative confrontation network model (Scene graph stack GAN, SGS-GAN) is proposed, which converts the text description into The scene graph uses the scene graph as the condition vector and inputs the random noise into the generator model to obtain the result image. The experimental results show that the Inception store of the SGS-GAN model on the Visual Genome and COCO data sets reached 6.64 and 6.52, respectively, which were increased by 0.212 and 0.219 compared to Sg2Im. This proves that the diversity and vividness of the generated samples and the sharpness of the image are obviously improved after the number of times of training and the input of the scene graph.","PeriodicalId":103309,"journal":{"name":"2020 2nd International Conference on Information Technology and Computer Application (ITCA)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124547941","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
A universal index for measuring network interconnectedness 一种衡量网络连通性的通用指标
2020 2nd International Conference on Information Technology and Computer Application (ITCA) Pub Date : 2020-12-01 DOI: 10.1109/ITCA52113.2020.00086
Bin Chen, Yiqun Zhao
{"title":"A universal index for measuring network interconnectedness","authors":"Bin Chen, Yiqun Zhao","doi":"10.1109/ITCA52113.2020.00086","DOIUrl":"https://doi.org/10.1109/ITCA52113.2020.00086","url":null,"abstract":"Traditionally, there were many indexes proposed for network interconnectedness measurement. But they were actually abused. These indexes were either for connected networks or for unconnected networks. There is still no index suitable for both connected networks and unconnected networks. To solve the problem, a new index is constructed for interconnectedness measurement by synthesizing the average shortest path length and the average number of disconnected node pairs. And the theory how to construct it and why it is correct is illustrated systematically. At last, a case is adopted to test and verify the validity of the proposed index.","PeriodicalId":103309,"journal":{"name":"2020 2nd International Conference on Information Technology and Computer Application (ITCA)","volume":"543 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123375585","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: 0
Rapid elimination of noise in 3D laser scanning point cloud data 三维激光扫描点云数据噪声的快速消除
2020 2nd International Conference on Information Technology and Computer Application (ITCA) Pub Date : 2020-12-01 DOI: 10.1109/itca52113.2020.00071
W. Weijie, Xue Hera, Z. Yanqing, Yang Tong
{"title":"Rapid elimination of noise in 3D laser scanning point cloud data","authors":"W. Weijie, Xue Hera, Z. Yanqing, Yang Tong","doi":"10.1109/itca52113.2020.00071","DOIUrl":"https://doi.org/10.1109/itca52113.2020.00071","url":null,"abstract":"When using a hand-held 3D laser scanner to collect target object data, due to factors such as personnel operation, collection environment and equipment itself, a large number of external noise points are often produced. This will seriously affect the processing and reconstruction accuracy of later point cloud data. According to the data analysis, these external noise points are divided into two categories: flying points and cluster points. Aiming at this phenomenon, a point cloud model noise removal algorithm combining statistical filtering and pass-through filtering is proposed. Firstly, the flying points are eliminated by statistical filtering, and then the remaining large area cluster points are removed by through filtering. The experimental results show that the algorithm can quickly and accurately identify external noise points and eliminate them completely.","PeriodicalId":103309,"journal":{"name":"2020 2nd International Conference on Information Technology and Computer Application (ITCA)","volume":"116 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124136927","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: 0
首页 上一页 下一页 尾页
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整，为了账户安全，请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们：info@booksci.cn Book学术提供免费学术资源搜索服务，方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号：481959085
Book学术官方微信