{"title":"基于Apache Cassandra的OWL本体学习方法","authors":"N. Soe, Tin Tin Yee, Ei Chaw Htoon","doi":"10.1109/AITC.2019.8921025","DOIUrl":null,"url":null,"abstract":"Big Data is a massive volume of both unstructured and structured data. It is crucial to efficiently represent big data as knowledge for data management. Ontologies provide knowledge as a formal description of a domain of interest. Therefore, the ontology learning approach is proposed for Apache Cassandra. It is composed of six mapping rules and converts OWL ontology from data in Cassandra by applying these mapping rules. NorthWind dataset is applied for demonstrating how to learn ontology from data in Cassandra. The evaluation result indicates that our approach can learn ontology in covering terminologically the modeled domain since the adequacy of extracted ontology is greater than 15%.","PeriodicalId":388642,"journal":{"name":"2019 International Conference on Advanced Information Technologies (ICAIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"C2Ont: An OWL Ontology Learning Approach from Apache Cassandra\",\"authors\":\"N. Soe, Tin Tin Yee, Ei Chaw Htoon\",\"doi\":\"10.1109/AITC.2019.8921025\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Big Data is a massive volume of both unstructured and structured data. It is crucial to efficiently represent big data as knowledge for data management. Ontologies provide knowledge as a formal description of a domain of interest. Therefore, the ontology learning approach is proposed for Apache Cassandra. It is composed of six mapping rules and converts OWL ontology from data in Cassandra by applying these mapping rules. NorthWind dataset is applied for demonstrating how to learn ontology from data in Cassandra. The evaluation result indicates that our approach can learn ontology in covering terminologically the modeled domain since the adequacy of extracted ontology is greater than 15%.\",\"PeriodicalId\":388642,\"journal\":{\"name\":\"2019 International Conference on Advanced Information Technologies (ICAIT)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Conference on Advanced Information Technologies (ICAIT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AITC.2019.8921025\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Advanced Information Technologies (ICAIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AITC.2019.8921025","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
C2Ont: An OWL Ontology Learning Approach from Apache Cassandra
Big Data is a massive volume of both unstructured and structured data. It is crucial to efficiently represent big data as knowledge for data management. Ontologies provide knowledge as a formal description of a domain of interest. Therefore, the ontology learning approach is proposed for Apache Cassandra. It is composed of six mapping rules and converts OWL ontology from data in Cassandra by applying these mapping rules. NorthWind dataset is applied for demonstrating how to learn ontology from data in Cassandra. The evaluation result indicates that our approach can learn ontology in covering terminologically the modeled domain since the adequacy of extracted ontology is greater than 15%.
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