The New Algorithms Of Machine Learning For Education People With Special Needs
| Parent link: | The European Proceedings of Social & Behavioural Sciences (EpSBS) Vol. 38 : Lifelong Wellbeing in the World (WELLSO 2017).— 2018.— [P. 206-215] |
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| المؤلف الرئيسي: | |
| مؤلفون مشاركون: | , |
| مؤلفون آخرون: | |
| الملخص: | Title screen The paper addresses the problem of adapting people with special needs to their environment. We support the idea that organizing special algorithms will be a solution to this problem. The analysis of people behavior in the actual learning process and their e-learning experience shows their ability to adjust their actions and develop adaptation skills relevant to any environment. Furthermore, we analyze the ways to involve people with special needs into the virtual setting activities, thus enabling them to feel that they are productive employees and members of the society. We present the detailed algorithm of the intellectual research, where each step affects the overall decision-making process. Participants, including those with special needs, can also correct their decisions, which helps them develop their abilities to adapt to their future working environment in a company. The main advantage of arranging such process in the electronic environment is that people with special needs acquire the adaptation, communication and decision-making skills as part of machine learning. The analysis of the subject area was carried out, and the main problems of creating automated systems for searching competency development tasks were considered. Also the methods that are used for reference systems (collaborative filtering), information semantic search, and separation of texts on topics without training are presented. |
| اللغة: | الإنجليزية |
| منشور في: |
2018
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| الموضوعات: | |
| الوصول للمادة أونلاين: | http://dx.doi.org/10.15405/epsbs.2018.04.24 http://earchive.tpu.ru/handle/11683/47226 |
| التنسيق: | الكتروني فصل الكتاب |
| KOHA link: | https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=658062 |
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| 200 | 1 | |a The New Algorithms Of Machine Learning For Education People With Special Needs |f A. V. Khaperskaya, O. G. Berestneva | |
| 203 | |a Text |c electronic | ||
| 300 | |a Title screen | ||
| 320 | |a [References: p. 215 (8 tit.)] | ||
| 330 | |a The paper addresses the problem of adapting people with special needs to their environment. We support the idea that organizing special algorithms will be a solution to this problem. The analysis of people behavior in the actual learning process and their e-learning experience shows their ability to adjust their actions and develop adaptation skills relevant to any environment. Furthermore, we analyze the ways to involve people with special needs into the virtual setting activities, thus enabling them to feel that they are productive employees and members of the society. We present the detailed algorithm of the intellectual research, where each step affects the overall decision-making process. Participants, including those with special needs, can also correct their decisions, which helps them develop their abilities to adapt to their future working environment in a company. The main advantage of arranging such process in the electronic environment is that people with special needs acquire the adaptation, communication and decision-making skills as part of machine learning. The analysis of the subject area was carried out, and the main problems of creating automated systems for searching competency development tasks were considered. Also the methods that are used for reference systems (collaborative filtering), information semantic search, and separation of texts on topics without training are presented. | ||
| 461 | 0 | |0 (RuTPU)RU\TPU\network\11959 |t The European Proceedings of Social & Behavioural Sciences (EpSBS) | |
| 463 | 0 | |0 (RuTPU)RU\TPU\network\25098 |t Vol. 38 : Lifelong Wellbeing in the World (WELLSO 2017) |o IV International Scientific Symposium, 11-15 September 2017, Tomsk, Russian Federation |o [proceedings] |f National Research Tomsk Polytechnic University (TPU) ; eds. F. Casati, G. A. Barysheva, W. Krieger |v [P. 206-215] |d 2018 | |
| 610 | 1 | |a электронный ресурс | |
| 610 | 1 | |a труды учёных ТПУ | |
| 610 | 1 | |a semantic analysis | |
| 610 | 1 | |a disable people | |
| 610 | 1 | |a competences | |
| 610 | 1 | |a lsa-algorithm | |
| 610 | 1 | |a data mining | |
| 610 | 1 | |a machine learning | |
| 610 | 1 | |a семантический анализ | |
| 610 | 1 | |a компетенции | |
| 610 | 1 | |a интеллектуальный анализ | |
| 610 | 1 | |a машинное обучение | |
| 610 | 1 | |a алгоритмы | |
| 610 | 1 | |a электронное обучение | |
| 700 | 1 | |a Khaperskaya |b A. V. |c economist |c Associate Professor of Tomsk Polytechnic University, Candidate of Pedagogical Sciences |f 1986- |g Alena Vasilievna |y Tomsk |3 (RuTPU)RU\TPU\pers\33542 |9 17209 | |
| 701 | 1 | |a Berestneva |b O. G. |c specialist in the field of informatics and computer technology |c Professor of Tomsk Polytechnic University, Doctor of technical sciences |f 1953- |g Olga Grigorievna |3 (RuTPU)RU\TPU\pers\30927 |9 15165 | |
| 712 | 0 | 2 | |a Национальный исследовательский Томский политехнический университет |b Школа базовой инженерной подготовки |b Отделение социально-гуманитарных наук |3 (RuTPU)RU\TPU\col\23512 |
| 712 | 0 | 2 | |a Национальный исследовательский Томский политехнический университет |b Инженерная школа информационных технологий и робототехники |b Отделение информационных технологий |3 (RuTPU)RU\TPU\col\23515 |
| 801 | 2 | |a RU |b 63413507 |c 20180518 |g RCR | |
| 856 | 4 | |u http://dx.doi.org/10.15405/epsbs.2018.04.24 | |
| 856 | 4 | |u http://earchive.tpu.ru/handle/11683/47226 | |
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