dc.contributor.author | Golovianko, Mariia | |
dc.contributor.author | Gryshko, Svitlana | |
dc.contributor.author | Terziyan, Vagan | |
dc.contributor.editor | Szymański, Julian | |
dc.contributor.editor | Velegrakis, Yannis | |
dc.date.accessioned | 2018-02-20T11:52:14Z | |
dc.date.available | 2018-02-20T11:52:14Z | |
dc.date.issued | 2018 | |
dc.identifier.citation | Golovianko, 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.other | CONVID_27901497 | |
dc.identifier.other | TUTKAID_76808 | |
dc.identifier.uri | https://jyx.jyu.fi/handle/123456789/57128 | |
dc.description.abstract | Search 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.extent | 261 | |
dc.language.iso | eng | |
dc.publisher | Springer | |
dc.relation.ispartof | Semantic Keyword-Based Search on Structured Data Sources. IKC 2017 | |
dc.relation.ispartofseries | Lecture Notes in Computer Science | |
dc.subject.other | syväoppiminen | |
dc.subject.other | deep learning | |
dc.subject.other | cognitive system | |
dc.subject.other | computational creativity | |
dc.subject.other | exploratory search | |
dc.subject.other | deep university | |
dc.title | From Deep Learning to Deep University : Cognitive Development of Intelligent Systems | |
dc.type | conferenceObject | |
dc.identifier.urn | URN:NBN:fi:jyu-201802151497 | |
dc.contributor.laitos | Informaatioteknologian tiedekunta | fi |
dc.contributor.laitos | Faculty of Information Technology | en |
dc.contributor.oppiaine | Tietotekniikka | fi |
dc.contributor.oppiaine | Mathematical Information Technology | en |
dc.type.uri | http://purl.org/eprint/type/ConferencePaper | |
dc.date.updated | 2018-02-15T13:15:08Z | |
dc.relation.isbn | 978-3-319-74496-4 | |
dc.description.reviewstatus | peerReviewed | |
dc.format.pagerange | 80-85 | |
dc.relation.issn | 0302-9743 | |
dc.type.version | acceptedVersion | |
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.accesslevel | openAccess | fi |
dc.relation.conference | International Keystone conference | |
dc.subject.yso | kognitiivinen kehitys | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p15532 | |
dc.relation.doi | 10.1007/978-3-319-74497-1_8 | |