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Titlebook: Innovations for Community Services; 17th International C Gerald Eichler,Christian Erfurth,Günter Fahrnberge Conference proceedings 2017 Spr

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發(fā)表于 2025-3-21 18:01:44 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Innovations for Community Services
副標(biāo)題17th International C
編輯Gerald Eichler,Christian Erfurth,Günter Fahrnberge
視頻videohttp://file.papertrans.cn/468/467011/467011.mp4
概述Includes supplementary material:
叢書名稱Communications in Computer and Information Science
圖書封面Titlebook: Innovations for Community Services; 17th International C Gerald Eichler,Christian Erfurth,Günter Fahrnberge Conference proceedings 2017 Spr
描述This book constitutes the refereed proceedings of the 17th International Conference on Innovations for Community Services, I4CS 2017, held in Darmstadt, Germany, in June 2017..The 12 revised full papers presented together with two short papers were carefully reviewed and selected from 31 submissions. The papers are organized in topical sections on?Social Networks;?Cooperative Networks;?Optimization Algorithms;?Infrastructure Planning;?Energy Management;?Short Papers..
出版日期Conference proceedings 2017
關(guān)鍵詞ad hoc networks; algorithms; applied computing; artificial intelligence; data mining; information retriev
版次1
doihttps://doi.org/10.1007/978-3-319-60447-3
isbn_softcover978-3-319-60446-6
isbn_ebook978-3-319-60447-3Series ISSN 1865-0929 Series E-ISSN 1865-0937
issn_series 1865-0929
copyrightSpringer International Publishing AG 2017
The information of publication is updating

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https://doi.org/10.1007/978-3-319-60447-3ad hoc networks; algorithms; applied computing; artificial intelligence; data mining; information retriev
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Gerald Eichler,Christian Erfurth,Günter FahrnbergeIncludes supplementary material:
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Innovations for Community Services978-3-319-60447-3Series ISSN 1865-0929 Series E-ISSN 1865-0937
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Towards the Automatic Sentiment Analysis of German News and Forum Documentslenging task due to the domain-specific language style and the variety of sentiment indicators. The basis for learning powerful sentiment classifiers are annotated datasets, but for many domains and especially with non-English texts hardly any datasets exist. In order to support the development of s
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Concept of Observer to Detect Special Cases in a Multidimensional Datasetequire specific processing in social networks, medical applications or complex processes. This paper proposes to use the observer’s paradigm to detect special cases in a multidimensional data space. Thus the observations allow to define the neighborhoods of data. Then we propose a rareness index for
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