Knowledge Base Management System

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A Knowledge Base Management System is a database management system that solve a knowledge base management task (to manage a knowledge base).



References

2003

  •  (Hicks, 2003) ⇒ Richard C. Hicks. (2003). “Knowledge base management systems-tools for creating verified intelligent systems" In: Knowledge-based Systems, 16(3). doi:10.1016/S0950-7051(02)00082-5
    • ABSTRACT: As automation of business processes becomes more complex and encompasses less-structured domains, it becomes even more essential that the knowledge used by these processes is verified and accurate. Most application development is facilitated with software tools, but most business rules and expert systems are developed in environments that provide inadequate verification testing. This paper describes an emerging class of applications we refer to as Knowledge Base Management Systems (KBMS). The KMBS provides a full life-cycle environment for the development and verification of business rule and expert systems. We will present an overview of knowledge base verification, the KBMS life-cycle, and the architecture for a KBMS. We then describe building a small expert system in the KBMS, with emphasis on the verification testing at each stage. We conclude with a summary of the benefits of a KBMS.

1999

  • (Andrade & Saltz, 1999) ⇒ Henrique Andrade, and Joel H. Saltz. (1999). “Towards a Knowledge Base Management System (KBMS): An Ontology-Aware Database Management System (DBMS)" In: Brazilian Symposium on Databases - SBBD.
    •  http://academic.research.microsoft.com/Publication/241414/towards-a-knowledge-base-management-system-kbms-an-ontology-aware-database-management-system
    • ABSTRACT: This paper aims to provide limited knowledge awareness to a conventional DBMS (Database Management Systems). This goal is achieved by extending an off-the-shelf DBMS (Postgresql in our case) in such way that it becomes ontology aware. The concept of ontology is used in our approach as a way of formalizing knowledge and relationships among objects in a domain of interest. Our solution is compounded by two main pieces: an external knowledge server and a set of functions to extend the DBMS. We argue that our solution is both powerful in the sense of supporting knowledge retrieval in the queries, and generic, in the sense that it can be deployed in any DBMS with the support for user-defined functions. Two application domains that can benefit from our approach are data mining and ad hoc query processing in hypothesis exploration environments (e.g. medical research). We also argue that our approach is original in how it pushes a conventional DBMS towards having features like the ones expected from Knowledge Base Management Systems (KBMS).

1993