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Thinking lifecycle as an implementation of machine understanding in software maintenance automation domain

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dc.contributor.author Toschev A.
dc.contributor.author Talanov M.
dc.date.accessioned 2018-09-18T20:49:08Z
dc.date.available 2018-09-18T20:49:08Z
dc.date.issued 2015
dc.identifier.issn 2190-3018
dc.identifier.uri https://dspace.kpfu.ru/xmlui/handle/net/142482
dc.description.abstract © Springer International Publishing Switzerland 2015. The main goal of our work is to test the feasibility study of automation of incident processing in Infrastructure as Service domain to optimize the operational costs of management services that are delivered remotely. This paper also describes a framework that authors have developed to deliver an integrated incident, problem solution and resolution approach as an event-driven Automated Incident Solving System, for Remote Infrastructure Management (RIM) Model. Current approaches are mainly automated scripts, but this is a specific approach for one specific problem. Those systems can’t think. Our approach is a system that exploits a thinking model thus can think and can learn. In other words system is capable of recombining its knowledge to solve new problems. Based on Minsky [11] thinking model we have created a machine understanding prototype which is capable of learning and understanding primitive incident description texts.
dc.relation.ispartofseries Smart Innovation, Systems and Technologies
dc.subject Artificial intelligence
dc.subject Automation
dc.subject Intelligent agents
dc.subject Knowledge base
dc.subject Machine understanding
dc.subject NLP
dc.subject Reasoning
dc.subject Remote infrastructure management
dc.title Thinking lifecycle as an implementation of machine understanding in software maintenance automation domain
dc.type Conference Paper
dc.relation.ispartofseries-volume 38
dc.collection Публикации сотрудников КФУ
dc.relation.startpage 301
dc.source.id SCOPUS21903018-2015-38-SID84947904510

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  • Публикации сотрудников КФУ Scopus [22633]
    Коллекция содержит публикации сотрудников Казанского федерального (до 2010 года Казанского государственного) университета, проиндексированные в БД Scopus, начиная с 1970г.

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