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dc.contributor.authorGolovianko, Mariia
dc.contributor.authorGryshko, Svitlana
dc.contributor.authorTerziyan, Vagan
dc.contributor.editorSzymański, Julian
dc.contributor.editorVelegrakis, Yannis
dc.date.accessioned2018-02-20T11:52:14Z
dc.date.available2018-02-20T11:52:14Z
dc.date.issued2018
dc.identifier.citationGolovianko, M., Gryshko, S., & Terziyan, V. (2018). From Deep Learning to Deep University : Cognitive Development of Intelligent Systems. In J. Szymański, & Y. Velegrakis (Eds.), <i>Semantic Keyword-Based Search on Structured Data Sources. IKC 2017</i> (pp. 80-85). Springer. Lecture Notes in Computer Science, 10546. <a href="https://doi.org/10.1007/978-3-319-74497-1_8" target="_blank">https://doi.org/10.1007/978-3-319-74497-1_8</a>
dc.identifier.otherCONVID_27901497
dc.identifier.otherTUTKAID_76808
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/57128
dc.description.abstractSearch is not only an instrument to find intended information. Ability to search is a basic cognitive skill helping people to explore the world. It is largely based on personal intuition and creativity. However, due to the emerged big data challenge, people require new forms of training to develop or improve this ability. Current developments within Cognitive Computing and Deep Learning enable artificial systems to learn and gain human-like cognitive abilities. This means that the skill how to search efficiently and creatively within huge data spaces becomes one of the most important ones for the cognitive systems aiming at autonomy. This skill cannot be pre-programmed, it requires learning. We offer to use the collective search expertise to train creative association-driven navigation across heterogeneous information spaces. We argue that artificial cognitive systems, as well as humans, need special environments, like universities, to train skills of autonomy and creativity.
dc.format.extent261
dc.language.isoeng
dc.publisherSpringer
dc.relation.ispartofSemantic Keyword-Based Search on Structured Data Sources. IKC 2017
dc.relation.ispartofseriesLecture Notes in Computer Science
dc.subject.othersyväoppiminen
dc.subject.otherdeep learning
dc.subject.othercognitive system
dc.subject.othercomputational creativity
dc.subject.otherexploratory search
dc.subject.otherdeep university
dc.titleFrom Deep Learning to Deep University : Cognitive Development of Intelligent Systems
dc.typeconferenceObject
dc.identifier.urnURN:NBN:fi:jyu-201802151497
dc.contributor.laitosInformaatioteknologian tiedekuntafi
dc.contributor.laitosFaculty of Information Technologyen
dc.contributor.oppiaineTietotekniikkafi
dc.contributor.oppiaineMathematical Information Technologyen
dc.type.urihttp://purl.org/eprint/type/ConferencePaper
dc.date.updated2018-02-15T13:15:08Z
dc.relation.isbn978-3-319-74496-4
dc.type.coarhttp://purl.org/coar/resource_type/c_5794
dc.description.reviewstatuspeerReviewed
dc.format.pagerange80-85
dc.relation.issn0302-9743
dc.type.versionacceptedVersion
dc.rights.copyright© Springer International Publishing AG, part of Springer Nature 2018. This is a final draft version of an article whose final and definitive form has been published by Springer. Published in this repository with the kind permission of the publisher.
dc.rights.accesslevelopenAccessfi
dc.relation.conferenceInternational Keystone conference
dc.subject.ysokognitiivinen kehitys
jyx.subject.urihttp://www.yso.fi/onto/yso/p15532
dc.relation.doi10.1007/978-3-319-74497-1_8
dc.type.okmA4


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