標題: Titlebook: Distributed Computing in Big Data Analytics; Concepts, Technologi Sourav Mazumder,Robin Singh Bhadoria,Ganesh Chandr Book 2017 Springer Int [打印本頁] 作者: 熱情美女 時間: 2025-3-21 19:43
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作者: 賄賂 時間: 2025-3-21 21:00
Why Elizabeth Never Left EnglandThose concepts are used in various Big Data Technologies of present time, which are in turn the key building blocks of the Big Data Analytics used today in various businesses and industries. So it is essential for practitioners of Big Data Analytics to understand these fundamental concepts related t作者: commute 時間: 2025-3-22 00:58
Time Study and Methods Improvementing models, system architectures, and platforms for the development of distributed systems. Several Big Data frameworks of today implement these concepts of distributed system for data synchronization, message exchange, real time data processing and transaction control in architectures for Big Data 作者: 你敢命令 時間: 2025-3-22 05:37 作者: 類人猿 時間: 2025-3-22 08:54 作者: 施舍 時間: 2025-3-22 13:57
Wage Payment Plans and Incentivese, nonlinear and non-stationary in their dynamics. Solutions to these problems often necessitate the use of complex mathematical modeling, simulation and analysis which are traditionally achieved by the use of expensive high performance computing, more commonly known as Super-Computers. In this chap作者: 施舍 時間: 2025-3-22 17:24
https://doi.org/10.1007/978-3-030-00163-6 industries such as travel and transport. However, in last year or two this phrase has gone viral across various business industries with experts predicting that the cognitive systems will play a very vital role in next generation of computing in general and especially in Big Data Analytics. In this作者: ascetic 時間: 2025-3-23 00:49
Alberto M. Goldwaser,Eric L. Goldwaserctively use social media today. This abrupt societal transition has led to a dramatic increase in the extent to which a person’s social footprint is documented online in the public domain. While for some social media sites, like Snapchat and Facebook, privacy is a key feature, on sites like Twitter,作者: 盟軍 時間: 2025-3-23 01:58 作者: Gentry 時間: 2025-3-23 09:16
https://doi.org/10.1007/978-3-319-59834-5Distributed computing; Cognitive analytics; Internet of things; Social media analytics; Scientific data 作者: 左右連貫 時間: 2025-3-23 10:13 作者: synovitis 時間: 2025-3-23 15:36
Sourav Mazumder,Robin Singh Bhadoria,Ganesh ChandrAddresses key concepts and patterns of distributed computing to provide practitioners with insight while designing big data analytics use cases.Details how different big data technologies leverage tho作者: 不可侵犯 時間: 2025-3-23 20:53
Scalable Computing and Communicationshttp://image.papertrans.cn/e/image/281859.jpg作者: 木訥 時間: 2025-3-23 23:21 作者: 名字 時間: 2025-3-24 02:49 作者: 任命 時間: 2025-3-24 08:53
https://doi.org/10.1007/978-3-030-00163-6 various technologies and methodologies in the cognitive analytics space. Finally we will discuss specific use cases being implemented currently in the enterprises in the areas of Health Care, Internet Of Things and Customer Care.作者: Ige326 時間: 2025-3-24 11:40 作者: 粘連 時間: 2025-3-24 15:18 作者: 拋射物 時間: 2025-3-24 20:16 作者: 指耕作 時間: 2025-3-25 02:41 作者: 性上癮 時間: 2025-3-25 06:20
Distributed Computing Patterns Useful in Big Data Analytics,Analytics applications. This Chapter discusses basic patterns of distributed systems, those abstract these concepts and can be used in homogeneous, heterogeneous or hybrid environments of Big Data Analytics implementations.作者: IRK 時間: 2025-3-25 09:52
Fundamental Concepts of Distributed Computing Used in Big Data Analytics,ay in various businesses and industries. So it is essential for practitioners of Big Data Analytics to understand these fundamental concepts related to Distributed Computing. In this chapter we cover these fundamental concepts of Distributed Computing along with the Quality of Service aspects associated with them with examples wherever applicable.作者: adhesive 時間: 2025-3-25 12:29 作者: 縱火 時間: 2025-3-25 19:06
Book 2017making. Principles of distributed computing are the keys to big data technologies and analytics. The mechanisms related to data storage, data access, data transfer, visualization and predictive modeling using distributed processing in multiple low cost machines are the key considerations that make b作者: 他一致 時間: 2025-3-25 22:34
On the Role of Distributed Computing in Big Data Analytics, of data. The explosion of devices that have automated and perhaps improved the lives of all of us has generated a huge mass of information that will continue to grow exponentially. For this reason, the need to store, manage, and treat the ever increasing amounts of data has become urgent. The chall作者: Musket 時間: 2025-3-26 02:25 作者: annexation 時間: 2025-3-26 05:42 作者: hankering 時間: 2025-3-26 10:59
Distributed Computing Technologies in Big Data Analytics,dapted to create a new class of distributed computing platform and software components that make the big data analytics easier to implement. In this chapter, we discuss few of these technologies. First, we discuss the distributed database technology and how this technology has been adapted to develo作者: 權(quán)宜之計 時間: 2025-3-26 15:42 作者: 法律的瑕疵 時間: 2025-3-26 17:20 作者: Connotation 時間: 2025-3-26 23:14 作者: 善變 時間: 2025-3-27 02:28 作者: AORTA 時間: 2025-3-27 07:52
Utilizing Big Data Analytics for Automatic Building of Language-agnostic Semantic Knowledge Bases,matic techniques such as clustering or dimensionality reduction to discover latent semantic links within the content of a given corpus. The former is very labor intensive and is hard to maintain, while the latter is prone to noise and may be hard for a human to understand or to interact with directl作者: milligram 時間: 2025-3-27 11:15 作者: intention 時間: 2025-3-27 14:15 作者: Extemporize 時間: 2025-3-27 17:59
Scientific Computing and Big Data Analytics: Application in Climate Science,e delve into the details of how significantly large-sized data from the output of a complex fluid dynamics based Earth’s Climate Model can be processed using Distributed Technology framework, Spark, in an integrated manner with the final analytics results accessed by an web application for the end u作者: 結(jié)果 時間: 2025-3-27 23:08
Distributed Computing in Social Media Analytics,le industries where organizations are using aggregate social polling as input to demand forecasting solutions. Data for social analytics is largely unstructured and the social graph is massive. As a result, the choice of analytics techniques can have an enormous impact on the quality of the results 作者: 不遵守 時間: 2025-3-28 03:57 作者: 代替 時間: 2025-3-28 06:53
2520-8632 ata analytics. This book discusses also covers the main technologies which support distributed processing. Finally, this book provides insight into applications of big data analytics, highlighting how principle978-3-319-86713-7978-3-319-59834-5Series ISSN 2520-8632 Series E-ISSN 2364-9496 作者: 拱墻 時間: 2025-3-28 11:42 作者: 無意 時間: 2025-3-28 18:34 作者: Cerumen 時間: 2025-3-28 22:20
Wage Payment Plans and Incentivese delve into the details of how significantly large-sized data from the output of a complex fluid dynamics based Earth’s Climate Model can be processed using Distributed Technology framework, Spark, in an integrated manner with the final analytics results accessed by an web application for the end u作者: impale 時間: 2025-3-29 01:30
Alberto M. Goldwaser,Eric L. Goldwaserle industries where organizations are using aggregate social polling as input to demand forecasting solutions. Data for social analytics is largely unstructured and the social graph is massive. As a result, the choice of analytics techniques can have an enormous impact on the quality of the results
