{"title":"通过流处理集成AI和DBMS","authors":"D. S. Parker","doi":"10.1109/ICDE.1989.47224","DOIUrl":null,"url":null,"abstract":"An approach is presented for integrating AI (artificial intelligence) systems with DBMS (database management systems). The impedance mismatch that has made this integration a problem is, in essence, a difference in the two system models of data processing. The present approach is to avoid the mismatch by forcing both AI systems and DBMS into the common model of stream processing. The approach taken in the Tangram project at UCLA, which integrates Prolog with relational DBMS, is described. Prolog is extended to a functional language called Log(F) that facilitates development of stream processing programs. The integration of this system with DBMS is simultaneously elegant, easy to use, and relatively efficient.<<ETX>>","PeriodicalId":329505,"journal":{"name":"[1989] Proceedings. Fifth International Conference on Data Engineering","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1989-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Integrating AI and DBMS through stream processing\",\"authors\":\"D. S. Parker\",\"doi\":\"10.1109/ICDE.1989.47224\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An approach is presented for integrating AI (artificial intelligence) systems with DBMS (database management systems). The impedance mismatch that has made this integration a problem is, in essence, a difference in the two system models of data processing. The present approach is to avoid the mismatch by forcing both AI systems and DBMS into the common model of stream processing. The approach taken in the Tangram project at UCLA, which integrates Prolog with relational DBMS, is described. Prolog is extended to a functional language called Log(F) that facilitates development of stream processing programs. The integration of this system with DBMS is simultaneously elegant, easy to use, and relatively efficient.<<ETX>>\",\"PeriodicalId\":329505,\"journal\":{\"name\":\"[1989] Proceedings. Fifth International Conference on Data Engineering\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1989-02-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"[1989] Proceedings. Fifth International Conference on Data Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDE.1989.47224\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"[1989] Proceedings. Fifth International Conference on Data Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDE.1989.47224","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An approach is presented for integrating AI (artificial intelligence) systems with DBMS (database management systems). The impedance mismatch that has made this integration a problem is, in essence, a difference in the two system models of data processing. The present approach is to avoid the mismatch by forcing both AI systems and DBMS into the common model of stream processing. The approach taken in the Tangram project at UCLA, which integrates Prolog with relational DBMS, is described. Prolog is extended to a functional language called Log(F) that facilitates development of stream processing programs. The integration of this system with DBMS is simultaneously elegant, easy to use, and relatively efficient.<>
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