ENSURING DATA UNIQUENESS IN SEMANTIC NETWORKS

Abstract

The article gives a brief description of knowledge representation models. Atoms of meaning (basic, minimal informational units) combined with each other to express a common meaning represent knowledge (data about data, metadata). It is shown that most of the existing knowledge representation models are based on the network representation model. A method is proposed to ensure the uniqueness (originality) of a set of data underlying the network model of knowledge representation. To ensure the uniqueness of knowledge representation by a set of data, the article proposes to use the main theorem of arithmetic: data are denoted by simple numbers (identifiers); when multiplying among themselves several prime numbers (data identifiers) in their totality conveying the aggregate semantic meaning, a natural number is obtained, which is an identifier of knowledge. The use of the basic theorem of arithmetic also provides a formalization of important data properties: internal interpretability, structuredness, connectivity, semantic metrics and activity. The presence of these properties in the data indicates that it is already data over data, or in other words, knowledge. In certain cases, this can reduce the computational complexity of the algorithm of the linguistic processor.