{"title":"Lifting preferences to the semantic web: PreferenceSPARQL","authors":"M. Endres, Stefan Schödel, Klaus Emathinger","doi":"10.1145/3410566.3410590","DOIUrl":null,"url":null,"abstract":"PreferenceSQL is an SQL extension for standard relational databases supporting soft constraints and is used to find relevant data intuitively. Meanwhile, the Semantic Web has interoperability advantages and helps to retrieve information with machine-readable data. We use the benefits of both technologies by combining preferences from SQL with SPARQL, the query language of the Semantic Web. This work provides implementation details in Apache Jena for the new composite called 'PreferenceSPARQL'. Furthermore, we contribute comprehensive benchmarks that show which preference algorithm is best suited for our approach.","PeriodicalId":137708,"journal":{"name":"Proceedings of the 24th Symposium on International Database Engineering & Applications","volume":"2013 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 24th Symposium on International Database Engineering & Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3410566.3410590","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
PreferenceSQL is an SQL extension for standard relational databases supporting soft constraints and is used to find relevant data intuitively. Meanwhile, the Semantic Web has interoperability advantages and helps to retrieve information with machine-readable data. We use the benefits of both technologies by combining preferences from SQL with SPARQL, the query language of the Semantic Web. This work provides implementation details in Apache Jena for the new composite called 'PreferenceSPARQL'. Furthermore, we contribute comprehensive benchmarks that show which preference algorithm is best suited for our approach.
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