標題: Titlebook: Development Methodologies for Big Data Analytics Systems; Plan-driven, Agile, Manuel Mora,Fen Wang,Hector Duran-Limon Book 2024 The Editor [打印本頁] 作者: dilate 時間: 2025-3-21 16:58
書目名稱Development Methodologies for Big Data Analytics Systems影響因子(影響力)
書目名稱Development Methodologies for Big Data Analytics Systems影響因子(影響力)學科排名
書目名稱Development Methodologies for Big Data Analytics Systems網絡公開度
書目名稱Development Methodologies for Big Data Analytics Systems網絡公開度學科排名
書目名稱Development Methodologies for Big Data Analytics Systems被引頻次
書目名稱Development Methodologies for Big Data Analytics Systems被引頻次學科排名
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書目名稱Development Methodologies for Big Data Analytics Systems年度引用學科排名
書目名稱Development Methodologies for Big Data Analytics Systems讀者反饋
書目名稱Development Methodologies for Big Data Analytics Systems讀者反饋學科排名
作者: 連鎖,連串 時間: 2025-3-21 20:16 作者: FLORA 時間: 2025-3-22 03:07 作者: vertebrate 時間: 2025-3-22 05:34 作者: 石墨 時間: 2025-3-22 08:55
A Selective Conceptual Review of CRISP-DM and DDSL Development Methodologies for Big Data Analyticsre still scarce in the literature. In this chapter, we address this knowledge gap, and using the ISO/IEC 29110 standard – Basic profile – as a theoretical expected lightweight development process, we report a selective conceptual review between CRISP-DM – the main rigor-oriented BDAS methodology – a作者: 高腳酒杯 時間: 2025-3-22 14:34 作者: 高腳酒杯 時間: 2025-3-22 19:58 作者: 為寵愛 時間: 2025-3-23 00:23
Big Data Adoption Factors and Development Methodologies: A Multiple Case Study Analysis,m-size teams. They have used agile development methodology that enabled them to create rapid development, continuous improvement, increased stakeholder participation, and ability to develop with incomplete big data expertise. It also has some challenges that include repeated conflict, feature intera作者: 慟哭 時間: 2025-3-23 05:03 作者: muffler 時間: 2025-3-23 07:54 作者: meritorious 時間: 2025-3-23 09:51 作者: Axillary 時間: 2025-3-23 14:04 作者: 紡織品 時間: 2025-3-23 20:54
Ashwin Alias,R. Abhijith,Vineetha Thankachanally framed using a generic BDAS pipeline derived from the main BDAS literature and the new NIST Big Data Reference Architecture (NBDRA). Our descriptive review, thus, provides theoretical and practical insights for implementing BDAS services.作者: 小教堂 時間: 2025-3-23 22:20 作者: cruise 時間: 2025-3-24 03:40
Green Business Process Managementng, Cham, 2020), inter alia), or experimentation (RapidMiner, Orange, Weka, Tensorflow, etc.), but we are not aware of any management tools that tie them together and ensure methodology compliance. To the best of our knowledge, to date, no requirement analysis exists for a system that meets the need作者: conflate 時間: 2025-3-24 10:06
Der neue Goldrausch: Green to Gold,re still scarce in the literature. In this chapter, we address this knowledge gap, and using the ISO/IEC 29110 standard – Basic profile – as a theoretical expected lightweight development process, we report a selective conceptual review between CRISP-DM – the main rigor-oriented BDAS methodology – a作者: 猛然一拉 時間: 2025-3-24 12:37
https://doi.org/10.1007/978-3-031-54188-9 vs. lightweight or agile BDAS development methodologies are still scarce in the literature. In this chapter, we address this knowledge gap, and we report a comparative review between CRISP-DM – the main rigor-oriented BDAS methodology – and Team Data Science Process (TDSP), a new relevant proprieta作者: 偶然 時間: 2025-3-24 18:51 作者: 聯(lián)想記憶 時間: 2025-3-24 19:43
Amandine L. Flourat,Florent Allaism-size teams. They have used agile development methodology that enabled them to create rapid development, continuous improvement, increased stakeholder participation, and ability to develop with incomplete big data expertise. It also has some challenges that include repeated conflict, feature intera作者: 恭維 時間: 2025-3-25 00:23
Jean-Marie Chauvet,Honorine Lescieux-Katirf the lesion. For both datasets, the same preprocessing approach was used to enhance image quality. This involved normalizing the images and applying contrast limited adaptive histogram equalization (CLAHE). The efficacy of the preprocessing techniques was evaluated by comparing the performance of t作者: Flat-Feet 時間: 2025-3-25 04:46 作者: 蜈蚣 時間: 2025-3-25 10:04 作者: reaching 時間: 2025-3-25 15:36 作者: BAIL 時間: 2025-3-25 17:21 作者: 令人心醉 時間: 2025-3-25 20:14 作者: Increment 時間: 2025-3-26 00:30
A Selective Conceptual Review of CRISP-DM and DDSL Development Methodologies for Big Data Analyticsal and external to the organization, with descriptive, predictive, or prescriptive purposes. BDAS are relevant software systems pursued in diverse domains of application such as marketing, healthcare, finance, manufacturing, logistics, education, and tourism, among others. However, despite BDAS bein作者: 公式 時間: 2025-3-26 06:07 作者: 試驗 時間: 2025-3-26 10:35 作者: FRAUD 時間: 2025-3-26 13:30 作者: 發(fā)牢騷 時間: 2025-3-26 19:04
Detection of Breast Cancer in Mammography Using Pretrained Convolutional Neural Networks with Fine-ential diagnostic tool in detecting breast cancer, but interpreting mammogram images can be challenging due to their complex nature. To assist radiologists in identifying abnormalities in mammogram images, deep learning algorithms, specifically deep convolutional neural networks (DCNNs), are being e作者: 蛙鳴聲 時間: 2025-3-26 23:53 作者: 與野獸博斗者 時間: 2025-3-27 02:59 作者: 呼吸 時間: 2025-3-27 07:33 作者: Brittle 時間: 2025-3-27 11:52 作者: inveigh 時間: 2025-3-27 16:21 作者: BUST 時間: 2025-3-27 21:16
Green Business Process Managementelopment of machine learning models in their organizational context. While the existing proposals vary with respect to complexity and suitability for particular tasks, it would be desirable to have software tools that embody and support these methodologies and make it easier for project teams to cap作者: 彩色的蠟筆 時間: 2025-3-27 23:50
Der neue Goldrausch: Green to Gold,al and external to the organization, with descriptive, predictive, or prescriptive purposes. BDAS are relevant software systems pursued in diverse domains of application such as marketing, healthcare, finance, manufacturing, logistics, education, and tourism, among others. However, despite BDAS bein作者: 山頂可休息 時間: 2025-3-28 06:00 作者: PLE 時間: 2025-3-28 10:08
Jean-Marie Chauvet,Honorine Lescieux-Katir theory to practice, to address the research questions of the main concepts and evolution (RQ.1), the most relevant frameworks (RQ.2), the main domains of applications reported (RQ.3), and the main trends and challenges for effective decisional support with BDA systems (RQ.4). This involves utilizin作者: guardianship 時間: 2025-3-28 12:11 作者: Asseverate 時間: 2025-3-28 14:39
Jean-Marie Chauvet,Honorine Lescieux-Katirential diagnostic tool in detecting breast cancer, but interpreting mammogram images can be challenging due to their complex nature. To assist radiologists in identifying abnormalities in mammogram images, deep learning algorithms, specifically deep convolutional neural networks (DCNNs), are being e作者: 讓空氣進入 時間: 2025-3-28 20:37 作者: 附錄 時間: 2025-3-29 00:59
James J. Mousseau,Antonia F. Stepanal, education, sports, retail, and manufacturing, among others. Several domains such as marketing and logistics are using big data to make better decisions and gain competitive advantage (Du et al., Gen Hosp Psychiat 67: 144, 2020; Idemudia et al., Using information technology advancements to adapt 作者: GRIN 時間: 2025-3-29 03:13
https://doi.org/10.1007/978-3-031-40956-1Big Data Analytics Systems; Big Data Development Methodologies; CRISP-DM; SEMMA and KDD; Scrum; Agile pra作者: 沒有準備 時間: 2025-3-29 08:00
978-3-031-40958-5The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl作者: malign 時間: 2025-3-29 12:26
Manuel Mora,Fen Wang,Hector Duran-LimonAddresses the mathematical, statistical and computational foundations and techniques of Big Data Analytics.Includes specific research problems in the development methodologies from a Systems and Softw作者: 思考而得 時間: 2025-3-29 16:14
