Integrating AI and DBMS through stream processing

D. S. Parker
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引用次数: 7

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.<>
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通过流处理集成AI和DBMS
提出了一种人工智能系统与数据库管理系统集成的方法。使这种集成成为问题的阻抗不匹配,本质上是两种数据处理系统模型的差异。目前的方法是通过强制人工智能系统和DBMS进入流处理的公共模型来避免不匹配。本文描述了加州大学洛杉矶分校Tangram项目所采用的方法,该方法将Prolog与关系DBMS集成在一起。Prolog扩展为一种称为Log(F)的函数式语言,便于流处理程序的开发。该系统与DBMS的集成同时优雅,易于使用,并且相对高效。
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