Olegs Verhodubs

Olegs Verhodubs

Keyword search engines are essential elements of large information spaces. The largest information space is the Web, and keyword search engines play crucial role there. The advent of keyword search engines has provided a quantum leap in the development of the Web. Since then, the Web has continued to evolve, and keyword search systems have proven inadequate. A new quantum leap in the development of keyword search engines is needed. This quantum leap can be provided with more intellectual keyword search engines. The increased intelligence of such keyword search engines can be achieved through a combination of keyword search engines and expert systems. The paper reveals how it can be done.

Olegs Verhodubs

Ontology merging is important, but not always effective. The main reason, why ontology merging is not effective, is that ontology merging is performed without considering goals. Goals define the way, in which ontologies to be merged more effectively. The paper illustrates ontology merging by means of rules, which are generated from these ontologies. This is necessary for further use in expert systems.

Olegs Verhodubs

Experience is what makes our life more effective that is why it is necessary to share experience among people. The use of information technologies is the most technological way to work with experience, and the use of the Web is the best way for sharing it. This paper describes a web resource designed for storing, sharing and using experience that is obtained from different people in the Web. The main purpose of this paper is to present this web resource in order to evaluate the interest in such a web resource.

Olegs Verhodubs

This paper describes the realization of the Ontology Web Search Engine. The Ontology Web Search Engine is realizable as independent project and as a part of other projects. The main purpose of this paper is to present the Ontology Web Search Engine realization details as the part of the Semantic Web Expert System and to present the results of the Ontology Web Search Engine functioning. It is expected that the Semantic Web Expert System will be able to process ontologies from the Web, generate rules from these ontologies and develop its knowledge base.

Olegs Verhodubs

Information and knowledge are transformable into each other. Information transformation into knowledge by the example of rule generation from OWL (Web Ontology Language) ontology has been shown during the development of the SWES (Semantic Web Expert System). The SWES is expected as an expert system for searching OWL ontologies from the Web, generating rules from the found ontologies and supplementing the SWES knowledge base with these rules. The purpose of this paper is to show knowledge transformation into information by the example of ontology generation from rules.

Olegs Verhodubs

The project of the Ontology Web Search Engine is presented in this paper. The main purpose of this paper is to develop such a project that can be easily implemented. Ontology Web Search Engine is software to look for and index ontologies in the Web. OWL (Web Ontology Languages) ontologies are meant, and they are necessary for the functioning of the SWES (Semantic Web Expert System). SWES is an expert system that will use found ontologies from the Web, generating rules from them, and will supplement its knowledge base with these generated rules. It is expected that the SWES will serve as a universal expert system for the average user.

Olegs Verhodubs

This paper presents an idea of inductive learning use for rule generation from ontologies. The main purpose of the paper is to evaluate the possibility of inductive learning use in rule generation from ontologies and to develop the way how this can be done. Generated rules are necessary to supplement or even to develop the Semantic Web Expert System (SWES) knowledge base. The SWES emerges as the result of evolution of expert system concept toward the Web, and the SWES is based on the Semantic Web technologies. Available publications show that the problem of rule generation from ontologies based on inductive learning is not investigated deeply enough.

Olegs Verhodubs

This paper develops the idea of membership function assignment for OWL (Web Ontology Language) ontology elements in order to subsequently generate fuzzy rules from this ontology. The task of membership function assignment for OWL ontology elements had already been partially described, but this concerned the case, when several OWL ontologies of the same domain were available, and they were merged into a single ontology. The purpose of this paper is to present the way of membership function assignment for OWL ontology elements in the case, when there is the only one available ontology. Fuzzy rules, generated from the OWL ontology, are necessary for supplement of the SWES (Semantic Web Expert System) knowledge base. SWES is an expert system, which will be able to extract knowledge from OWL ontologies, found in the Web, and will serve as a universal expert for the user.

Olegs Verhodubs

This paper discloses the potential of OWL (Web Ontology Language) ontologies for generation of rules. The main purpose of this paper is to identify new types of rules, which may be generated from OWL ontologies. Rules, generated from OWL ontologies, are necessary for the functioning of the Semantic Web Expert System. It is expected that the Semantic Web Expert System (SWES) will be able to process ontologies from the Web with the purpose to supplement or even to develop its knowledge base.