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Titlebook: Next Generation Data Technologies for Collective Computational Intelligence; Nik Bessis,Fatos Xhafa Book 2011 Springer Berlin Heidelberg 2

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41#
發(fā)表于 2025-3-28 18:07:45 | 只看該作者
Spiros Nikolopoulos,Elisavet Chatzilari,Eirini Giannakidou,Symeon Papadopoulos,Ioannis Kompatsiaris,ingen Teil der Lebenszykluskosten (LZK) aus. Grund genug, die Nutzungskosten bspw. für Instandhaltung, Wartung oder Ersatzteile zu optimieren. Gerade im ?ffentlichen Sektor (Verteidigung, Stra?enbau usw.) sind Optimierungsans?tze für LZK besonders relevant. Die regulierte Beschaffungsumgebung erlaub
42#
發(fā)表于 2025-3-28 18:56:45 | 只看該作者
43#
發(fā)表于 2025-3-29 02:21:13 | 只看該作者
Building Collective Tag Intelligence through Folksonomy Coordinationh tags on the basis of available collective tag intelligence. Finally, we describe the evaluation of the proposed techniques over real datasets extracted from . and . folksonomies and a real application example of exploiting the collective tag intelligence for similarity-based resource retrieval.
44#
發(fā)表于 2025-3-29 03:34:41 | 只看該作者
45#
發(fā)表于 2025-3-29 08:31:28 | 只看該作者
1860-949X intelligence in a unified manner.Describe the incorporation.This book focuses on next generation data technologies in support of collective and computational intelligence. The book brings various next generation data technologies together to capture, integrate, analyze, mine, annotate and visualize
46#
發(fā)表于 2025-3-29 11:35:27 | 只看該作者
Book 2011on data technologies together to capture, integrate, analyze, mine, annotate and visualize distributed data – made available from various community users – in a meaningful and collaborative for the organization manner. A unique perspective on collective computational intelligence is offered by embra
47#
發(fā)表于 2025-3-29 17:46:30 | 只看該作者
Trust-Based Techniques for Collective Intelligence in Social Search Systemsapter provides an overview of the current landscape of computational models of trust and reputation, and it presents an experimental study case in the domain of social search, where we show how trust techniques can be applied to enhance the quality of social search engine predictions.
48#
發(fā)表于 2025-3-29 21:41:01 | 只看該作者
Visualising Computational Intelligence through Converting Data into Formal Conceptsby extract data’s inherent semantics. The chapter describes how this will be further developed in a project called “Combining and Uniting Business Intelligence with Semantic Technologies” (CUBIST), to provide in-data-warehouse visual analytics for Resource Description Framework (RDF)-based triple stores.
49#
發(fā)表于 2025-3-30 03:58:03 | 只看該作者
Decision Making under Synchronous Time Stress among Bilateral Decision Makersalways located at the one-third of the entire or remaining duration for decision procedures, instead of a heuristic point of its half time. We have conducted a feasibility check on the proposed formulas on cost of time and strategic points in their applications to a case study.
50#
發(fā)表于 2025-3-30 05:34:36 | 只看該作者
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