{"title":"llatesminer:一个多语言DSL,用于从llates平台提取信息","authors":"A. D. Alves, H. Yanasse, N. Y. Soma","doi":"10.1145/2095050.2095065","DOIUrl":null,"url":null,"abstract":"The Lattes CV system, a curricular information system maintained by CNPq, is the core of the Lattes Platform. This system is undoubtedly the major source of information on Brazilian researchers. This paper describes \"LattesMiner\", a multilingual domain-specific language for automatic information extraction from Lattes curricula. It is composed by a set of classes written in Java that allows developers to implement their own applications with a high-level abstraction and expression power. LattesMiner can extract data belonging to the Lattes Platform from any individual researcher or group of researchers by its name or given (ID) number. The data extracted can be analyzed and used, for instance, to identify academic social networks, regional competences, profile of groups in diferent areas of research etc. We illustrate its use with a case study.","PeriodicalId":143880,"journal":{"name":"SPLASH Workshops","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2011-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"LattesMiner: a multilingual DSL for information extraction from lattes platform\",\"authors\":\"A. D. Alves, H. Yanasse, N. Y. Soma\",\"doi\":\"10.1145/2095050.2095065\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Lattes CV system, a curricular information system maintained by CNPq, is the core of the Lattes Platform. This system is undoubtedly the major source of information on Brazilian researchers. This paper describes \\\"LattesMiner\\\", a multilingual domain-specific language for automatic information extraction from Lattes curricula. It is composed by a set of classes written in Java that allows developers to implement their own applications with a high-level abstraction and expression power. LattesMiner can extract data belonging to the Lattes Platform from any individual researcher or group of researchers by its name or given (ID) number. The data extracted can be analyzed and used, for instance, to identify academic social networks, regional competences, profile of groups in diferent areas of research etc. We illustrate its use with a case study.\",\"PeriodicalId\":143880,\"journal\":{\"name\":\"SPLASH Workshops\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-10-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"SPLASH Workshops\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2095050.2095065\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"SPLASH Workshops","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2095050.2095065","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
LattesMiner: a multilingual DSL for information extraction from lattes platform
The Lattes CV system, a curricular information system maintained by CNPq, is the core of the Lattes Platform. This system is undoubtedly the major source of information on Brazilian researchers. This paper describes "LattesMiner", a multilingual domain-specific language for automatic information extraction from Lattes curricula. It is composed by a set of classes written in Java that allows developers to implement their own applications with a high-level abstraction and expression power. LattesMiner can extract data belonging to the Lattes Platform from any individual researcher or group of researchers by its name or given (ID) number. The data extracted can be analyzed and used, for instance, to identify academic social networks, regional competences, profile of groups in diferent areas of research etc. We illustrate its use with a case study.