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Titlebook: Knowledge, Information and Creativity Support Systems; Selected Papers from Susumu Kunifuji,George Angelos Papadopoulos,Janusz Conference p

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書目名稱Knowledge, Information and Creativity Support Systems
副標(biāo)題Selected Papers from
編輯Susumu Kunifuji,George Angelos Papadopoulos,Janusz
視頻videohttp://file.papertrans.cn/545/544172/544172.mp4
概述Recent research in Knowledge, Information and Creativity Support Systems.Presents selected papers from KICSS’2014 - 9th International Conference, held in Limassol, Cyprus, on November 6-8, 2014.Presen
叢書名稱Advances in Intelligent Systems and Computing
圖書封面Titlebook: Knowledge, Information and Creativity Support Systems; Selected Papers from Susumu Kunifuji,George Angelos Papadopoulos,Janusz Conference p
描述.Thisvolume consists of a number of selected papers thatwere presented at the 9th International Conference on Knowledge, Informationand Creativity Support Systems (KICSS 2014) in Limassol, Cyprus, after theywere substantially revised and extended. The 26 regularpapers and 19 short papers included in this proceedings cover all aspects ofknowledge management, knowledge engineering, intelligent information systems,and creativity in an information technology context, including computationalcreativity and its cognitive and collaborative aspects.?.
出版日期Conference proceedings 2016
關(guān)鍵詞Knowledge Support Systems; Information Support Systems; Creativity Support Systems; Intelligent Systems
版次1
doihttps://doi.org/10.1007/978-3-319-27478-2
isbn_softcover978-3-319-27477-5
isbn_ebook978-3-319-27478-2Series ISSN 2194-5357 Series E-ISSN 2194-5365
issn_series 2194-5357
copyrightSpringer International Publishing Switzerland 2016
The information of publication is updating

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V. A. Shmelev,A. V. Dukhanov,K. V. Knyazkov,S. V. Ivanov
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Using Appropriate Context Models for CARS Context Modelling,xt model development with instructions to the developer, model comparison, useful statistics, recommendations of similar models, as well as alternative views of context models to aid the developer’s task.
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Application of Rough Sets in , Nearest Neighbours Algorithm for Classification of Incomplete Samplen set of classes. The important feature of the proposed system is, that it reduces the set of the possible classes and specifies the set of certain classes in the way of filling the missing values by set of possible values.
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