{"title":"介绍了新的SIM-DLA语义相似度度量插件,用于prot<s:1>本体编辑器","authors":"Christoph Mülligann, Johannes Trame, K. Janowicz","doi":"10.1145/2068976.2068979","DOIUrl":null,"url":null,"abstract":"Semantic similarity measurement has been an active research area in GIScience and the Semantic Web for many years. However, implementations of these measures were largely missing, not publicly available, or tailored to specific application needs. To foster the application of similarity reasoning in information retrieval, ontology engineering, and spatial decision support, we implemented the SIM-DL semantic similarity server as well as a plug-in for the popular Protégé ontology editor. While SIM-DL has been successfully applied to several application areas, the implemented similarity theory was largely structural, could not handle concept and instance similarity within the same framework, and was based on a Protégé version and DIG interface that have been re-engineered over the last years. This paper introduces a new version, called SIM-DLA, engineered from scratch to addresses these shortcomings. It is based on our new similarity theory, can handle inter-instance and inter-concept similarity using the same functions and alignments, and is available for the new Protégé version 4.1.","PeriodicalId":302720,"journal":{"name":"SSO '11","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Introducing the new SIM-DLA semantic similarity measurement plug-in for the Protégé ontology editor\",\"authors\":\"Christoph Mülligann, Johannes Trame, K. Janowicz\",\"doi\":\"10.1145/2068976.2068979\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Semantic similarity measurement has been an active research area in GIScience and the Semantic Web for many years. However, implementations of these measures were largely missing, not publicly available, or tailored to specific application needs. To foster the application of similarity reasoning in information retrieval, ontology engineering, and spatial decision support, we implemented the SIM-DL semantic similarity server as well as a plug-in for the popular Protégé ontology editor. While SIM-DL has been successfully applied to several application areas, the implemented similarity theory was largely structural, could not handle concept and instance similarity within the same framework, and was based on a Protégé version and DIG interface that have been re-engineered over the last years. This paper introduces a new version, called SIM-DLA, engineered from scratch to addresses these shortcomings. It is based on our new similarity theory, can handle inter-instance and inter-concept similarity using the same functions and alignments, and is available for the new Protégé version 4.1.\",\"PeriodicalId\":302720,\"journal\":{\"name\":\"SSO '11\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"SSO '11\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2068976.2068979\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"SSO '11","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2068976.2068979","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Introducing the new SIM-DLA semantic similarity measurement plug-in for the Protégé ontology editor
Semantic similarity measurement has been an active research area in GIScience and the Semantic Web for many years. However, implementations of these measures were largely missing, not publicly available, or tailored to specific application needs. To foster the application of similarity reasoning in information retrieval, ontology engineering, and spatial decision support, we implemented the SIM-DL semantic similarity server as well as a plug-in for the popular Protégé ontology editor. While SIM-DL has been successfully applied to several application areas, the implemented similarity theory was largely structural, could not handle concept and instance similarity within the same framework, and was based on a Protégé version and DIG interface that have been re-engineered over the last years. This paper introduces a new version, called SIM-DLA, engineered from scratch to addresses these shortcomings. It is based on our new similarity theory, can handle inter-instance and inter-concept similarity using the same functions and alignments, and is available for the new Protégé version 4.1.