scholarly journals A Clustering Method for Information Summarization and Modelling a Subject Domain

2021 ◽  
Vol 50 ◽  
pp. 79-86
Author(s):  
Dmytro Lande ◽  
Ihor Subach ◽  
Olexander Puchkov ◽  
Artem Soboliev
Keyword(s):  
Subject Domain ◽  
Clustering Method

Modelling Subject Domain Causality for Learning Content Renewal

Informatica ◽  
2019 ◽  
Vol 30 (3) ◽  
pp. 455-480 ◽  
Author(s):  
Saulius Gudas ◽  
Jurij Tekutov ◽  
Rimantas Butleris ◽  
Vitalijus Denisovas
Keyword(s):  
Subject Domain ◽  
Learning Content

Use of ontological analysis for competence evaluation of scientists in a particular subject domain

2016 ◽  
pp. 081-096
Author(s):  
J.V. Rogushina ◽  
Keyword(s):  
Scientific Activity ◽  
Subject Domain ◽  
Semantic Matching ◽  
Research Project ◽  
Open Environment ◽  
Competence Evaluation ◽  
The Subject ◽  
Ontological Analysis ◽  
Use Of Knowledge ◽  
The Web

Objective methods for competence evaluating of scientists in the subject domain pertinent to the specific scientific product – research project, publication, etc. are proposed. These methods are based on the semantic matching of the description of scientific product and documents that confirm the competence of its authors or experts in the domain of this product. In addition, the use of knowledge acquired from the Web open environment – Wiki-resources, scientometric databases, organization official website, domain ontologies is proposed. Specialized ontology of scientific activity which allows to standardize the terminological base for describing the qualifications of researchers is developed.

THE METHODS OF A RESEARCH OF PROCESSES OF SPONTANEOUS SOCIALIZATION BASED ON NONCLASSICAL APPROACH

2020 ◽  
Vol 22 (12) ◽  
pp. 34-38
Author(s):  
Abashina A.D.
Keyword(s):  
Methodological Approach ◽  
Social Situation ◽  
Subject Domain ◽  
Child Research ◽  
Research Problems ◽  
Internet Environment ◽  
Anthropological Approach ◽  
Research Complex ◽  
Methodological Approaches ◽  
The Individual

Relevance and statement of a problem. Now processes of socialization of younger generation undergo profound changes. They are characterized by transformation of space-time characteristics – narrowing of the field purposeful, expansion of processes of spontaneous socialization. At the same time the methodological approaches and methods of a research aimed at the analysis of the static phenomena applied in pedagogics become insufficient for a research of chaotic processes. There is a need for search of methodology and methods of a research within which the analysis of processes of spontaneous socialization of modern children and teenagers is possible. Research search shows that the solution of this task is possible on the basis of nonclassical methodological approach. Research objective: identification of opportunities of nonclassical methodology for a research of processes of spontaneous socialization of the modern child. Research problems: representation of the methods in logic of nonclassical methodology aimed at the analysis of these processes. Object and subject of research: the situation of development of the child which is characterized by experiences concerning the relations and readiness for an exception of social interaction in various spheres of activity and immersion in the Internet environment. Subject domain of a research: complex of the relations which are the cornerstone of purposeful and spontaneous socialization of the teenager. Research methodology - nonclassical (anthropological) approach. Research materials. In the course of work on a problem the research methods based mainly on the individual and communicative practicians aimed at the analysis of experiences and communication of the child were developed. Results of a research. The qualitative methods based nonclassical approach will allow to understand not only experiences of the child, but also as negative trends under what conditions they lead to break in relations and to search of significant network contacts that is under what conditions processes of purposeful socialization are weakened collect in his social situation of development, extend borders of socialization spontaneous.

Teknik Data Mining Dalam Clustering Produksi Susu Segar Di Indonesia Dengan Algoritma K-Means

2019 ◽  
Vol 1 (1) ◽  
pp. 31-39
Author(s):  
Ilham Safitra Damanik ◽  
Sundari Retno Andani ◽  
Dedi Sehendro
Keyword(s):  
Data Mining ◽  
Milk Production ◽  
Clustering Algorithm ◽  
Clustering Method ◽  
Data Mining Techniques ◽  
Low Level ◽  
Fresh Milk ◽  
Nutritional Needs ◽  
High Level ◽  
Level Cluster

Milk is an important intake to meet nutritional needs. Both consumed by children, and adults. Indonesia has many producers of fresh milk, but it is not sufficient for national milk needs. Data mining is a science in the field of computers that is widely used in research. one of the data mining techniques is Clustering. Clustering is a method by grouping data. The Clustering method will be more optimal if you use a lot of data. Data to be used are provincial data in Indonesia from 2000 to 2017 obtained from the Central Statistics Agency. The results of this study are in Clusters based on 2 milk-producing groups, namely high-dairy producers and low-milk producing regions. From 27 data on fresh milk production in Indonesia, two high-level provinces can be obtained, namely: West Java and East Java. And 25 others were added in 7 provinces which did not follow the calculation of the K-Means Clustering Algorithm, including in the low level cluster.

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