{"title":"基于关联规则挖掘的文献综述分析新方法","authors":"Samia Laghrabli, L. Benabbou, A. Berrado","doi":"10.1109/SITA.2015.7358394","DOIUrl":null,"url":null,"abstract":"Literature review is important for laying a strong foundation for scientific research. Summarizing previous studies, evaluating them and assessing their advantages, gaps and opportunities are key steps to progress in research. Multiple types of literature reviews have been developed and massively used in the past. This paper focuses on the quantitative literature reviews and reinforces available analysis methods with a new framework. The suggested methodology is based on association rules analysis. It brings a novel approach for analyzing data and exploring new research tracks by bringing to evidence the different relationships existing between the studied variables. An example is presented at the end of this paper to illustrate the framework.","PeriodicalId":174405,"journal":{"name":"2015 10th International Conference on Intelligent Systems: Theories and Applications (SITA)","volume":"701 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"A new methodology for literature review analysis using association rules mining\",\"authors\":\"Samia Laghrabli, L. Benabbou, A. Berrado\",\"doi\":\"10.1109/SITA.2015.7358394\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Literature review is important for laying a strong foundation for scientific research. Summarizing previous studies, evaluating them and assessing their advantages, gaps and opportunities are key steps to progress in research. Multiple types of literature reviews have been developed and massively used in the past. This paper focuses on the quantitative literature reviews and reinforces available analysis methods with a new framework. The suggested methodology is based on association rules analysis. It brings a novel approach for analyzing data and exploring new research tracks by bringing to evidence the different relationships existing between the studied variables. An example is presented at the end of this paper to illustrate the framework.\",\"PeriodicalId\":174405,\"journal\":{\"name\":\"2015 10th International Conference on Intelligent Systems: Theories and Applications (SITA)\",\"volume\":\"701 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 10th International Conference on Intelligent Systems: Theories and Applications (SITA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SITA.2015.7358394\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 10th International Conference on Intelligent Systems: Theories and Applications (SITA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SITA.2015.7358394","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A new methodology for literature review analysis using association rules mining
Literature review is important for laying a strong foundation for scientific research. Summarizing previous studies, evaluating them and assessing their advantages, gaps and opportunities are key steps to progress in research. Multiple types of literature reviews have been developed and massively used in the past. This paper focuses on the quantitative literature reviews and reinforces available analysis methods with a new framework. The suggested methodology is based on association rules analysis. It brings a novel approach for analyzing data and exploring new research tracks by bringing to evidence the different relationships existing between the studied variables. An example is presented at the end of this paper to illustrate the framework.