{"title":"Extracting module from OWL-DL ontology","authors":"Liang Zhang, Kun Liu, Xue Qin, Shengqun Tang","doi":"10.1109/ICSSEM.2011.6081176","DOIUrl":null,"url":null,"abstract":"The use of ontologies lies at the very heart of the newly emerging era of semantic web. As information on the web increases significantly in size, web ontologies also tend to grow bigger, to such an extent that they become too large to be used in their entirety by any single application. Moreover, because of the size of the original ontology, the process of maintenance, reuse, reasoning and integration becomes very computationally extensive. Accordingly, the research community is increasing its effort towards the specification of frameworks and techniques that may help in downsizing ontology. Modularization is one of the approaches to achieve such a result. In this paper, we propose an algorithm of module extraction based on user's semantic query and realize it to a component of the framework for knowledge management system. Experiment shows that this approach is very useful in practice.","PeriodicalId":406311,"journal":{"name":"2011 International Conference on System science, Engineering design and Manufacturing informatization","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 International Conference on System science, Engineering design and Manufacturing informatization","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSSEM.2011.6081176","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
The use of ontologies lies at the very heart of the newly emerging era of semantic web. As information on the web increases significantly in size, web ontologies also tend to grow bigger, to such an extent that they become too large to be used in their entirety by any single application. Moreover, because of the size of the original ontology, the process of maintenance, reuse, reasoning and integration becomes very computationally extensive. Accordingly, the research community is increasing its effort towards the specification of frameworks and techniques that may help in downsizing ontology. Modularization is one of the approaches to achieve such a result. In this paper, we propose an algorithm of module extraction based on user's semantic query and realize it to a component of the framework for knowledge management system. Experiment shows that this approach is very useful in practice.