Titlebook: Business Intelligence; 4th European Summer Esteban Zimányi,Ralf-Detlef Kutsche Textbook 2015 Springer Nature Switzerland AG 2015 Big Data.

Cession

書目名稱Business Intelligence影響因子(影響力)




書目名稱Business Intelligence影響因子(影響力)學(xué)科排名




書目名稱Business Intelligence網(wǎng)絡(luò)公開度




書目名稱Business Intelligence網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Business Intelligence被引頻次




書目名稱Business Intelligence被引頻次學(xué)科排名




書目名稱Business Intelligence年度引用




書目名稱Business Intelligence年度引用學(xué)科排名




書目名稱Business Intelligence讀者反饋




書目名稱Business Intelligence讀者反饋學(xué)科排名

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Implicit

1865-1348 topics including requirements engineering for decision-support systems, visual analytics of large data sets, linked data and semantic technologies, supervised classification on data streams, and knowledge reuse in large organizations..978-3-319-17550-8978-3-319-17551-5Series ISSN 1865-1348 Series E-ISSN 1865-1356

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Vaginismus

https://doi.org/10.1007/978-4-431-92691-7namic social network, web mining, etc. The volume of data increases rapidly and it is now necessary to use incremental learning algorithms on data streams. This article presents the main approaches of incremental supervised classification available in the literature. It aims to give basic knowledge to a reader novice in this subject.

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組裝

-Deficient Medaka Created by TILLING fill this gap, we demonstrate a workflow of a comprehensive analysis of a publicly available data set about mobile phone calls of a large population over a long time period. We pay special attention to the evaluation of data properties. We outline potential applications of the proposed methods.

Inflated

Multi-perspective Analysis of Mobile Phone Call Data Records: A Visual Analytics Approach, fill this gap, we demonstrate a workflow of a comprehensive analysis of a publicly available data set about mobile phone calls of a large population over a long time period. We pay special attention to the evaluation of data properties. We outline potential applications of the proposed methods.

insurgent

,Künstliche Intelligenz in der Medizin,amework was followed. This paper describes the results of applying the framework in this project. Thus, it focuses on the requirements engineering stage. The difficulties found motivated the further study and analysis of the complexity of requirements engineering in decision-support systems and the feasibility of using said framework.

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