{"title":"A Methodology for Mapping Educational Domain Ontologies Using Top Level Ontologies","authors":"T. Ivanova","doi":"10.1109/InfoTech55606.2022.9897119","DOIUrl":"https://doi.org/10.1109/InfoTech55606.2022.9897119","url":null,"abstract":"A grand variety of ontology mapping methods algorithms and tools have been proposed recently, but no one can guarantee the automatically-generated alignment’s correctness and completeness. In this paper we discuss usefulness of the usage of ontologies and thesauruses as background knowledge for ontology mapping and propose a methodology for educational ontology mapping using such background knowledge.","PeriodicalId":196547,"journal":{"name":"2022 International Conference on Information Technologies (InfoTech)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128045436","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
N. Rezova, Lev Kazakovtsev, Guzel Shkaberina, D. Demidko, A. Goroshko
{"title":"Data Pre-Processing for Ecosystem Behavior Analysis","authors":"N. Rezova, Lev Kazakovtsev, Guzel Shkaberina, D. Demidko, A. Goroshko","doi":"10.1109/InfoTech55606.2022.9897105","DOIUrl":"https://doi.org/10.1109/InfoTech55606.2022.9897105","url":null,"abstract":"This paper discusses the application of data pre-processing methods to identify significant taxation and bioclimatic factors influencing the behavior of ecosystems, using examples of outbreaks of mass reproduction of the Siberian silk moth. For further analysis of the behavior of ecosystems, we formulate the problem of classification; we make a preliminary assessment of the methods of classification. As a classification method, we chose the decision tree method. The results of the computational experiment showed the expediency of data preprocessing for solving the problem of classifying large amounts of data.","PeriodicalId":196547,"journal":{"name":"2022 International Conference on Information Technologies (InfoTech)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134319343","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Optimization of hyperparameters with constraints on time and memory for the classification model of the hard drives states","authors":"Liliya A. Demidova, A. Filatov","doi":"10.1109/InfoTech55606.2022.9897074","DOIUrl":"https://doi.org/10.1109/InfoTech55606.2022.9897074","url":null,"abstract":"This article explores the issues of hyperparameters optimization of machine learning classification models under time and memory constraints A number of methods for optimizing hyperparameters of classification models in the learning process are considered: RandomSearch, GridSearch, TPE, CMA-ES. The effectiveness of these optimization methods is tested in the context of the task of classifying the states of hard disks. The construction and creation of classification models is based on two machine learning algorithms: LSTM and Random Forest. The hyperparameters of the proposed classification models are optimized based on the above methods. The models are trained on a public dataset from BackBlaze cloud storage. The article provides estimates of the values of the main indicators of classification quality, a comparative analysis of optimization methods is carried out. The experimental results confirm the feasibility of using optimization methods under time and memory constraints. Of particular note is the TPE method, which outperformed other methods in achieving the task of maximizing classification quality indicators.","PeriodicalId":196547,"journal":{"name":"2022 International Conference on Information Technologies (InfoTech)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121455861","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Algorithmization of the Process of Recognition of Biological Objects by Computed Tomography","authors":"T. Petrova, Z. Petrov","doi":"10.1109/InfoTech55606.2022.9897075","DOIUrl":"https://doi.org/10.1109/InfoTech55606.2022.9897075","url":null,"abstract":"This paper studies the results from the development of a model of a system for disease diagnosis based on an analytical method by image segmentation. Image segmentation has shown excellent efficiency for processing images acquired by computed tomography. The proposed model of a system for diagnosis has substantially enlarged the possibilities for an integrated approach when solving problems and discovering pathologies. This model has been tested on a computed tomography image – human brain with lesion.","PeriodicalId":196547,"journal":{"name":"2022 International Conference on Information Technologies (InfoTech)","volume":"3 9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123695855","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Lyubomir Blagoev, R. Trifonov, Kamen Boyanov Spassov
{"title":"A Set of Registers Supporting Semantic Interoperability in the E-governance’s Environment","authors":"Lyubomir Blagoev, R. Trifonov, Kamen Boyanov Spassov","doi":"10.1109/InfoTech55606.2022.9897110","DOIUrl":"https://doi.org/10.1109/InfoTech55606.2022.9897110","url":null,"abstract":"The process of establishing and maintaining the Semantic Interoperability (SI) is essentially a standardization process. In order to be successfully implemented, it is necessary to develop not only the standardization requirements but also the environment in which they will be presented, as well as the means by which their implementation will be controlled. In the case of SI for e-Governance, this environment has to be also under the same requirements for SI. Therefore, the most appropriate implementation of this environment is the registry form with full support of the connectivity between data in the registries.","PeriodicalId":196547,"journal":{"name":"2022 International Conference on Information Technologies (InfoTech)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123449893","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Investigation of Network Communications by Using Statistical Processing of Monitored Data","authors":"R. Romansky","doi":"10.1109/InfoTech55606.2022.9897115","DOIUrl":"https://doi.org/10.1109/InfoTech55606.2022.9897115","url":null,"abstract":"The communications in a given network structure are related to the generation of network traffic and one possibility for its investigation is to conduct program monitoring with subsequent statistical processing of the registered data. The article presents a study of communication parameters of traffic based on measurement experiments in a universal network segment and analysis of the formed sample to determine statistical estimates to detect relationships between parameters.","PeriodicalId":196547,"journal":{"name":"2022 International Conference on Information Technologies (InfoTech)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133722937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Ontology Mapping for Personalization in Adaptive E-learning","authors":"T. Ivanova","doi":"10.1109/InfoTech55606.2022.9897096","DOIUrl":"https://doi.org/10.1109/InfoTech55606.2022.9897096","url":null,"abstract":"Ontology mapping is critical in personalized learning for ontology-based information integration, e-learning systems interoperability, resources searching, recommendation and reuse. In this work we analyze and discuss ontology mapping methods, techniques strategies and its applicability and usefulness in e-learning domain. We also outline trends and discuss problems, related to ontology mapping in e-learning context.","PeriodicalId":196547,"journal":{"name":"2022 International Conference on Information Technologies (InfoTech)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130457127","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}