F. P. Romero, J. A. Olivas, M. Genero, M. Piattini
{"title":"Automatic extraction of the main terminology used in empirical software engineering through text mining techniques","authors":"F. P. Romero, J. A. Olivas, M. Genero, M. Piattini","doi":"10.1145/1414004.1414082","DOIUrl":null,"url":null,"abstract":"The need for an explicit common terminology within Empirical Software Engineering (an ESE-Glossary of terms) was highlighted in the ISERN 2007 meeting [2]. The goal was to define a glossary of terms related to ESE based on an initial glossary published in http://lens-ese.cos.ufrj.br/wikiese. This initial glossary was built manually, based on expert knowledge. However, owing to the dynamic nature of the research works in ESE, this glossary must be dynamically updated with information extracted from the relevant documents in the research domain. Automation is, therefore, mandatory. We propose a text mining technique for the automatic extraction of the most relevant terms used in ESE documents. Our technique also provides the relationships between terms, with the degree of affinity between them. Our approach could, therefore, be useful in the improvement of the initial glossary of terms and in discovering relationships between terms.","PeriodicalId":124452,"journal":{"name":"International Symposium on Empirical Software Engineering and Measurement","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Symposium on Empirical Software Engineering and Measurement","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1414004.1414082","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12
Abstract
The need for an explicit common terminology within Empirical Software Engineering (an ESE-Glossary of terms) was highlighted in the ISERN 2007 meeting [2]. The goal was to define a glossary of terms related to ESE based on an initial glossary published in http://lens-ese.cos.ufrj.br/wikiese. This initial glossary was built manually, based on expert knowledge. However, owing to the dynamic nature of the research works in ESE, this glossary must be dynamically updated with information extracted from the relevant documents in the research domain. Automation is, therefore, mandatory. We propose a text mining technique for the automatic extraction of the most relevant terms used in ESE documents. Our technique also provides the relationships between terms, with the degree of affinity between them. Our approach could, therefore, be useful in the improvement of the initial glossary of terms and in discovering relationships between terms.