Development of methods and technologies for creating intelligent scientific and educational internet resources

<span lang="EN-US">Currently, there is an avalanche-like increase in the need for automatic text processing, respectively, new effective methods and tools for processing texts in natural language are emerging. Although these methods, tools and resources are mostly presented on the internet, many of them remain inaccessible to developers, since they are not systematized, distributed in various directories or on separate sites of both humanitarian and technical orientation. All this greatly complicates their search and practical use in conducting research in computational linguistics and developing applied systems for natural text processing. This paper is aimed at solving the need described above. The paper goal is to develop model of an intelligent information resource based on modern methods of natural language processing (IIR NLP). The main goal of IIR NLP is to render convenient valuable access for specialists in the field of computational linguistics. The originality of our proposed approach is that the developed ontology of the subject area “NLP” will be used to systematize all the above knowledge, data, information resources and organize meaningful access to them, and semantic web standards and technology tools will be used as a software basis.</span>

Section: Construction a Model Of Integrated Support For The Developme...mentioning

confidence: 99%

Development of an intelligent information resource model based on modern natural language processing methods

Sadirmekova

Sambetbayeva

Serikbayeva

et al. 2023

“…The use of such patterns not only improves the quality but also greatly facilitates the development of an ontology since it can involve experts in the modeled area who do not have the skills of ontology modeling. To assess the quality of the ontology was developed a methodology [27], on the basis of which the involved experts carried out an experimental assessment of the created ontology, including an assessment of the degree of agreement of the experts. Metrics for evaluating various ontology properties that do not require expert work are also considered.…”

Section: Development Of Ontologies Subject Area "Automatic Text Proce...mentioning

confidence: 99%

Ontology engineering of automatic text processing methods

Sadirmekova,

Tussupov,

Murzakhmetov

et al. 2023

<span lang="EN-US">Currently, ontologies are recognized as the most effective means of formalizing and systematizing knowledge and data in scientific subject area (SSA). Practice has shown that using ontology design patterns is effective in developing the ontology of scientific subject areas. This is due to the fact that scientific subject areas ontology, as a rule, contains a large number of typical fragments that are well described by patterns of ontology design. In the paper, we present an approach to ontology engineering of automatic text processing methods based on ontology design patterns. In order to get an ontology that would describe automatic text processing sufficiently fully, it is required to process a large number of scientific publications and information resources containing information from modeling area. It is possible to facilitate and speed up the process of updating ontology with information from such sources by using lexical and syntactic patterns of ontology design. Our ontology of automatic text processing will become the conceptual basis of an intelligent information resource on modern methods of automatic text processing, which will provide systematization of all information on these methods, its integration into a single information space, convenient navigation through it, as well as meaningful access to it.</span>

“…Software specialists replenish the ontology with actual data-class objects and their properties, and in this process, the use of content patterns when replenishing the SSA ontology is supported by a special data editor as shown in Figure 4 [27], [28]. In the ontology updating process, user selects the desired class from the presented hierarchy of ontology classes.…”

mentioning

confidence: 99%

Approach to automating the construction and completion of ontologies in a scientific subject field

Sadirmekova,

Murzakhmetov,

Abduvalova

et al. 2024

Domain ontologies facilitate the organization, sharing, and reuse of subject areas. Building a software ontology is labor-intensive and time-consuming. In the process of obtaining a software ontology, it is required to analyze a huge number of scientific publications relevant to the software being modeled. The process of ontology replenishing with information from a huge number of scientific publications can be facilitated and accelerated through the use of lexical-syntactic patterns of ontological design. In this paper, we consider the possibility of automated construction of scientific subject area ontologies based on a heterogeneous patterns system of ontological design. This system includes ontological design patterns and is intended for ontology developers. System also includes automatically built lexical and syntactic patterns, which help to automatic replenishment of the ontology with information extracted from natural language texts.