Inference in DX

　What is important in AI is to provide highly accurate inference results

That is.

The credibility of the results, how DX data is defined and handled.

In making inferences for providing results, the causal relationship of events is

It is important to clarify and define.

The events handled in DX are inheritance hierarchies that represent the inheritance (roots) of events,

Representing the composition (structure), by the structural hierarchy, the tree structure

It is expressed in.

This is an example of a means of transportation, but as a means of transportation,

There are aviation, land, sea, etc., and there are cars on land.

A car is composed of wheels, an engine, a chassis, etc.

In addition, the composition of the car is expressed as a structural hierarchy.

Examples of inheritance and structure hierarchies

In this inheritance hierarchy and structural hierarchy, events are classified,

Create a tree structure.

In the previous example, we took the car, which is a means of transportation,

By changing the object of the event based on the desired solution,

It is possible to respond in any case.

Based on the tree structure, define DX data,

We make inferences, but for the solution we want, the event,

How to subdivide both inheritance and structure,

The more misdefined or unambiguously defined, the more

The accuracy of the solution decreases.

Highly accurate inference results clarify the inheritance and structural hierarchy of events,

Much depends on the definition of DX data.