{"title":"基于本体的工程文献检索索引方法","authors":"Weiguang Fang, Yu Guo, W. Liao","doi":"10.1109/ICKEA.2016.7803013","DOIUrl":null,"url":null,"abstract":"Engineering documents are valued resources in the reuse of engineering knowledge and effective reuse of these documents depends on efficient retrieval. A semantic indexing method, which accomplished by utilizing state-of-the-art ontology technologies of Semantic Web, is proposed in this paper to handle the issues in engineering documents retrieval. Firstly, in order to represent the semantics embedded in design documents, a domain ontology is constructed by concepts hierarchy and ontology population. Secondly, ontology inference service is presented to fulfill keywords semantic extension. Combining with Lucene mechanism, the extended document index is constructed for retrieval application. Finally, the classical matching and ranking approaches are adopted to develop a prototype domain knowledge retrieval system.","PeriodicalId":241850,"journal":{"name":"2016 IEEE International Conference on Knowledge Engineering and Applications (ICKEA)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Ontology-based indexing method for engineering documents retrieval\",\"authors\":\"Weiguang Fang, Yu Guo, W. Liao\",\"doi\":\"10.1109/ICKEA.2016.7803013\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Engineering documents are valued resources in the reuse of engineering knowledge and effective reuse of these documents depends on efficient retrieval. A semantic indexing method, which accomplished by utilizing state-of-the-art ontology technologies of Semantic Web, is proposed in this paper to handle the issues in engineering documents retrieval. Firstly, in order to represent the semantics embedded in design documents, a domain ontology is constructed by concepts hierarchy and ontology population. Secondly, ontology inference service is presented to fulfill keywords semantic extension. Combining with Lucene mechanism, the extended document index is constructed for retrieval application. Finally, the classical matching and ranking approaches are adopted to develop a prototype domain knowledge retrieval system.\",\"PeriodicalId\":241850,\"journal\":{\"name\":\"2016 IEEE International Conference on Knowledge Engineering and Applications (ICKEA)\",\"volume\":\"36 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE International Conference on Knowledge Engineering and Applications (ICKEA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICKEA.2016.7803013\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE International Conference on Knowledge Engineering and Applications (ICKEA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICKEA.2016.7803013","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Ontology-based indexing method for engineering documents retrieval
Engineering documents are valued resources in the reuse of engineering knowledge and effective reuse of these documents depends on efficient retrieval. A semantic indexing method, which accomplished by utilizing state-of-the-art ontology technologies of Semantic Web, is proposed in this paper to handle the issues in engineering documents retrieval. Firstly, in order to represent the semantics embedded in design documents, a domain ontology is constructed by concepts hierarchy and ontology population. Secondly, ontology inference service is presented to fulfill keywords semantic extension. Combining with Lucene mechanism, the extended document index is constructed for retrieval application. Finally, the classical matching and ranking approaches are adopted to develop a prototype domain knowledge retrieval system.