Semantic Network

TEKNOLOJİ

 

The Semantic Web is also called Web 3.0. This enumeration places it within the four generations of the Web known to date.

 

Web 1.0 is referred to as the documentary web, where resources are published without any processing other than formatting and without any interaction other than enabling hypertext links.

 

In this generation of the web, there is no computer process that takes the document as its object, inspired by certain information that specifies its type, structure, terms or concepts.

If you want to implement an automated process, the only data you have is the content itself and the broadcast format specifications.

 

The main limitation faced by this approach is that the rendering performed cannot rely on what is known about the content. It should be a report and not a business card, it should mention certain concepts, comply with formatting standards.

 

In other words, Web 1.0 blindly performs its processing, not the meaning, taking into account only the encoding of the content.

 

Then came the idea to enrich these treatments with additional information from the meaning of these ingredients to make them more precise and efficient.

 

The question then is how to bring knowledge and penetrate processes. At this point, two complementary approaches emerge.

 

In the first case, users are considered part of the documentary process and their knowledge and skills can be trusted. The challenge is to allow them to add information to the content through their understanding and interpretation.

 

This will be the target of web 2.0, also known as the contributor web. Therefore, a photography site relies on descriptions written by Internet users. But we can also look at things differently.

 

Instead of activating the internet user, it is necessary to equip the machine. Instead, based on human interpretation, tools need to represent both available relevant information and expected interpretation of the content.

 

Succeeding in this dual task will be the goal of web 3.0. It designs tools that can both represent and benefit from this information and interpretation.

 

Finally, the environmental intelligence paradigm leads us to think of the Web not as a set of tools, but rather as components integrated into devices and objects around us.

 

This is web 4.0 or the symbiotic web. Environment objects communicate through web devices that they internalize within themselves.

Semantics

 

If we want to represent knowledge, interpret the content, what sense and understanding of meaning must we adopt?

 

We have two goals or constraints: on the one hand, to be able to explain the meaning of a content, and on the other hand, to make that explanation usable through computer processing.

 

Several approaches are possible.

 

A psychological approach where the meaning of a term is its mental representation. To agree on the same thing is to have the same mental representation of it.

 

We often find this approach in the cognitive sciences where meaning is in the head. Understanding the brain then makes it possible to grasp what it is thinking.

 

A linguistic approach in which the meaning of a term consists in its expression in other terms. This approach is found in linguistics, semiotics, particularly the semiotics of cultures that deal with the differential paradigm.

 

An ontological approach in which the meaning of a term is based on the object it denotes or can designate. This representative approach refers to the constraint of having an understanding of what exists or can exist in the world to understand what a language's expressions mean.

 

The syntactic form of a term or an expression that indicates or suggests that the meaning of a term is its logical form, essentially (ontologically).

 

semantic network examples

semantic network model

semantic network psychology

semantic network generator

semantic network in ai

advantages and disadvantages of semantic network

semantic network questions

example of semantic network in ai

 

Especially if we want to have an expression that faithfully reflects the semantics, this syntactic form must be explained in the formalisms of mathematical logic. In other words, expressing the meaning of a content is tantamount to translating it into a logical formalism.

 

This last approach presents many challenges. But from a Semantic Web perspective, it's undeniably productive.

 

Explaining the meaning is to explain the logical form, and the second is syntactic, as it makes it possible to actually solve the two difficulties mentioned above, it can be used with computer processing.

 

Considering that meaning is nothing but a logical restatement of the logical, meaning that meaning can only be captured by rewriting it logically, the formalist approach provides web 3.0 with scientific, methodological and technical content.

 

Therefore, in the remainder of this issue we will find presentations of formalized languages ​​such as RDF, OWL. Because these are languages ​​that will have the heavy task of making sense and being used by computer tools.

 

Dr.Yaşam Ayavefe