{"title":"基于用户行为的开源社区协同知识创新模式挖掘研究","authors":"Jun Wang, Hongde Liu, Yani Wang, Xinyu Liang","doi":"10.1117/12.2667729","DOIUrl":null,"url":null,"abstract":"Collaborative knowledge innovation activities are conducive to the rapid development of knowledge economy. However, because the collaborative knowledge innovation is usually hidden in the complex network information transmission process, the efficiency and quality of knowledge innovation behaviors may be greatly affected. We take collaborative innovation participants, collaborative innovation teams and collaborative innovation achievements as the constituent elements and construct the research framework of collaborative knowledge innovation mode mining. Then, we use Apriori algorithm to mine the collaborative knowledge innovation mode and obtain the transformation mode. The results show that when the main contributors to a project are high active users, the project has a greater probability of showing a trend of high innovation activity and is more likely to become a high-quality project. The findings will help to improve the collaborative knowledge innovation ability of online community platforms and the efficiency of knowledge diffusion.","PeriodicalId":345723,"journal":{"name":"Fifth International Conference on Computer Information Science and Artificial Intelligence","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research on collaborative knowledge innovation mode mining based on user behavior in open source community\",\"authors\":\"Jun Wang, Hongde Liu, Yani Wang, Xinyu Liang\",\"doi\":\"10.1117/12.2667729\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Collaborative knowledge innovation activities are conducive to the rapid development of knowledge economy. However, because the collaborative knowledge innovation is usually hidden in the complex network information transmission process, the efficiency and quality of knowledge innovation behaviors may be greatly affected. We take collaborative innovation participants, collaborative innovation teams and collaborative innovation achievements as the constituent elements and construct the research framework of collaborative knowledge innovation mode mining. Then, we use Apriori algorithm to mine the collaborative knowledge innovation mode and obtain the transformation mode. The results show that when the main contributors to a project are high active users, the project has a greater probability of showing a trend of high innovation activity and is more likely to become a high-quality project. The findings will help to improve the collaborative knowledge innovation ability of online community platforms and the efficiency of knowledge diffusion.\",\"PeriodicalId\":345723,\"journal\":{\"name\":\"Fifth International Conference on Computer Information Science and Artificial Intelligence\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-03-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Fifth International Conference on Computer Information Science and Artificial Intelligence\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1117/12.2667729\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Fifth International Conference on Computer Information Science and Artificial Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2667729","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on collaborative knowledge innovation mode mining based on user behavior in open source community
Collaborative knowledge innovation activities are conducive to the rapid development of knowledge economy. However, because the collaborative knowledge innovation is usually hidden in the complex network information transmission process, the efficiency and quality of knowledge innovation behaviors may be greatly affected. We take collaborative innovation participants, collaborative innovation teams and collaborative innovation achievements as the constituent elements and construct the research framework of collaborative knowledge innovation mode mining. Then, we use Apriori algorithm to mine the collaborative knowledge innovation mode and obtain the transformation mode. The results show that when the main contributors to a project are high active users, the project has a greater probability of showing a trend of high innovation activity and is more likely to become a high-quality project. The findings will help to improve the collaborative knowledge innovation ability of online community platforms and the efficiency of knowledge diffusion.