Neural Networks and Database Systems

TL;DR

This paper discusses integrating neural networks into object-oriented database systems by treating them as complex data objects, enabling unified storage and reasoning within the database environment.

Contribution

It presents a method for embedding neural networks as data objects in database systems, facilitating rule-based reasoning and unified knowledge management.

Findings

Neural networks can be stored as normal data objects in databases.

Networks serve as representations of intensional knowledge.

Unified view of knowledge base including neural networks and rules.

Abstract

Object-oriented database systems proved very valuable at handling and administrating complex objects. In the following guidelines for embedding neural networks into such systems are presented. It is our goal to treat networks as normal data in the database system. From the logical point of view, a neural network is a complex data value and can be stored as a normal data object. It is generally accepted that rule-based reasoning will play an important role in future database applications. The knowledge base consists of facts and rules, which are both stored and handled by the underlying database system. Neural networks can be seen as representation of intensional knowledge of intelligent database systems. So they are part of a rule based knowledge pool and can be used like conventional rules. The user has a unified view about his knowledge base regardless of the origin of the unique rules.