Design of Personalized Recommendation and Sharing Management System for Science and Technology Achievements based on WEBSOCKET Technology

IF 0.7 Q3 COMPUTER SCIENCE, THEORY & METHODS International Journal of Advanced Computer Science and Applications Pub Date : 2023-01-01 DOI:10.14569/ijacsa.2023.0140968
Shan Zuo, Kai Xiao, Taitian Mao
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Abstract

Scientific research is becoming more and more crucial to contemporary society as the backbone of the nation's innovation-driven development. The rapid growth of information technology and the rise of information technology in scientific research both contribute to the globalization of scientific research. Small research groups still don't have a place to showcase and share their accomplishments, though. In order to integrate scientific research information and combine personalised recommendation technology to suggest developments of interest to users through their historical behaviour data, the study proposes a personalised recommendation and sharing management system for scientific and technological achievements based on the Ruby on Rails framework. According to the testing results, the system had a 299ms request response time, a maximum 1KB request resource size, and a 20ms data transfer time. Additionally, the study's user-based collaborative filtering recommendation algorithm has an accuracy rate of 41% when the nearest neighbor parameter is set to 50, there are 10 information suggestions, and there are 0.7 training sets, which essentially satisfies the system criteria. In conclusion, the research suggested that a personalised recommendation and sharing management system for scientific and technological accomplishments can essentially satisfy the needs of small research teams to communicate and share scientific accomplishments, as well as realise the sharing of scientific achievements.
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基于WEBSOCKET技术的科技成果个性化推荐与共享管理系统设计
科学研究作为国家创新驱动发展的中坚力量,在当代社会越来越重要。信息技术的快速发展和信息技术在科学研究中的兴起,都促进了科学研究的全球化。然而,小型研究小组仍然没有一个地方来展示和分享他们的成就。为了整合科研信息,结合个性化推荐技术,通过用户的历史行为数据向用户推荐感兴趣的发展,本研究提出了一种基于Ruby on Rails框架的科技成果个性化推荐与分享管理系统。根据测试结果,系统的请求响应时间为299ms,请求资源大小最大为1KB,数据传输时间为20ms。此外,本研究基于用户的协同过滤推荐算法,当最近邻参数设置为50,有10个信息建议,有0.7个训练集时,准确率为41%,基本满足系统标准。综上所述,个性化科技成果推荐与分享管理系统能够从根本上满足小型科研团队交流与分享科技成果的需求,实现科技成果的共享。
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来源期刊
CiteScore
2.30
自引率
22.20%
发文量
519
期刊介绍: IJACSA is a scholarly computer science journal representing the best in research. Its mission is to provide an outlet for quality research to be publicised and published to a global audience. The journal aims to publish papers selected through rigorous double-blind peer review to ensure originality, timeliness, relevance, and readability. In sync with the Journal''s vision "to be a respected publication that publishes peer reviewed research articles, as well as review and survey papers contributed by International community of Authors", we have drawn reviewers and editors from Institutions and Universities across the globe. A double blind peer review process is conducted to ensure that we retain high standards. At IJACSA, we stand strong because we know that global challenges make way for new innovations, new ways and new talent. International Journal of Advanced Computer Science and Applications publishes carefully refereed research, review and survey papers which offer a significant contribution to the computer science literature, and which are of interest to a wide audience. Coverage extends to all main-stream branches of computer science and related applications
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