標題: Titlebook: Big Data Analytics: Systems, Algorithms, Applications; C.S.R. Prabhu,Aneesh Sreevallabh Chivukula,L.M. Je Textbook 2019 Springer Nature Si [打印本頁] 作者: 要求 時間: 2025-3-21 16:41
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書目名稱Big Data Analytics: Systems, Algorithms, Applications讀者反饋學科排名
作者: 絆住 時間: 2025-3-22 00:12 作者: 承認 時間: 2025-3-22 01:38 作者: ventilate 時間: 2025-3-22 05:18
https://doi.org/10.1007/978-981-15-0094-7Big Data; Machine Learning; Internet of Things; Hadoop; NoSQL; Fog Computing作者: BUDGE 時間: 2025-3-22 10:38 作者: Aesthete 時間: 2025-3-22 15:25
On Exponentials and Logarithms,The latest disruptive trends and developments in digital age comprise social networking, mobility, analytics and cloud, popularly known as SMAC. The year 2016 saw Big Data Technologies being leveraged to power business intelligence applications. What holds in store for 2020 and beyond?作者: 真實的人 時間: 2025-3-22 20:45
Introduction to Analysis of the InfiniteThe ultimate goal of data science is to turn raw data into data products. Data analytics is the science of examining the raw data with the purpose of making correct decisions by drawing meaningful conclusions.作者: 大喘氣 時間: 2025-3-23 01:18 作者: 有節(jié)制 時間: 2025-3-23 02:43
On Exponentials and Logarithms,In the context of Big Data Analytics and Social Networking, Semantic Web Mining is an amalgamation of three scientific areas of research: (1) Social Networking (2) Semantic Web and (3) Big Data Analytics, including Web Mining and Data Mining.作者: 固定某物 時間: 2025-3-23 09:17
Introduction to Analysis of the InfiniteHaving surveyed in the last chapter how Big Data Analytics is applied in Social Semantic Web, in this chapter we shall delve into another very important application domain, IOT. We shall examine the interaction between IOT and Big Data Analytics.作者: FATAL 時間: 2025-3-23 12:10
On Exponentials and Logarithms,Having surveyed the applications of Big Data Analytics in Banking and Financial Services sector in the last chapter, we shall now provide an overview of the possible applications of Big Data Analytics in the Capital Market Use cases.作者: 劇毒 時間: 2025-3-23 17:33
https://doi.org/10.1007/978-1-4612-1021-4In the last few chapters, we have seen the application of Big Data Analytics to various application domains. In this chapter, we shall examine its role in insurance.作者: GROSS 時間: 2025-3-23 20:06
Big Data Analytics,The latest disruptive trends and developments in digital age comprise social networking, mobility, analytics and cloud, popularly known as SMAC. The year 2016 saw Big Data Technologies being leveraged to power business intelligence applications. What holds in store for 2020 and beyond?作者: 單片眼鏡 時間: 2025-3-23 23:19 作者: enhance 時間: 2025-3-24 04:17
,Big Data Tools—Hadoop Ecosystem, Spark and NoSQL Databases,In Chap. ., we have surveyed in brief the total overview for Big Data and Hadoop.作者: zonules 時間: 2025-3-24 08:09
Social Semantic Web Mining and Big Data Analytics,In the context of Big Data Analytics and Social Networking, Semantic Web Mining is an amalgamation of three scientific areas of research: (1) Social Networking (2) Semantic Web and (3) Big Data Analytics, including Web Mining and Data Mining.作者: 可卡 時間: 2025-3-24 11:35 作者: meritorious 時間: 2025-3-24 16:41 作者: seduce 時間: 2025-3-24 22:01
Big Data Analytics for Insurance,In the last few chapters, we have seen the application of Big Data Analytics to various application domains. In this chapter, we shall examine its role in insurance.作者: 知識分子 時間: 2025-3-25 02:39 作者: VEIL 時間: 2025-3-25 07:10 作者: FLAGR 時間: 2025-3-25 10:08 作者: cognizant 時間: 2025-3-25 14:49 作者: 高爾夫 時間: 2025-3-25 17:13 作者: Surgeon 時間: 2025-3-25 22:25
https://doi.org/10.1007/978-1-4612-1021-4finition, an algorithm is a sequence of steps in a computer program that transforms given input into desired output. Machine learning is the study of artificially intelligent algorithms that improve their performance at some task with experience. With the availability of big data, machine learning i作者: Fillet,Filet 時間: 2025-3-26 01:01 作者: CORE 時間: 2025-3-26 08:12 作者: 致詞 時間: 2025-3-26 08:30
On Series Which Arise From Products, the application of Big Data Analytics techniques is impacting the financial services and banking section. In a highly competitive business of financial services, we have companies vying with each other to grab their potential customers. This calls for their monitoring closely the customer opinions 作者: 偏狂癥 時間: 2025-3-26 12:52 作者: OATH 時間: 2025-3-26 20:49 作者: Vital-Signs 時間: 2025-3-26 22:39 作者: Desert 時間: 2025-3-27 02:42 作者: 壓迫 時間: 2025-3-27 08:26 作者: finale 時間: 2025-3-27 10:24
https://doi.org/10.1007/978-1-4612-1021-4ecently published in conferences such as ACM International Conference on Knowledge Discovery and Data Mining (ACM SIG KDD), SIAM International Conference on Data Mining (SDM), IEEE International Conference on Data Engineering (ICDE) and ACM International Conference on Information and Knowledge Manag作者: 驕傲 時間: 2025-3-27 16:40
a pursued by programmers, scientists, and managers.DocumentsThis book provides a comprehensive survey of techniques, technologies and applications of Big Data and its analysis. The Big Data phenomenon is increasingly impacting all sectors of business and industry, producing an emerging new informati作者: calumniate 時間: 2025-3-27 20:33 作者: BAIT 時間: 2025-3-27 22:33 作者: 不確定 時間: 2025-3-28 03:14 作者: 信條 時間: 2025-3-28 09:27
https://doi.org/10.1007/978-1-4612-1021-4nce on Data Mining (SDM), IEEE International Conference on Data Engineering (ICDE) and ACM International Conference on Information and Knowledge Management (CIKM). In this chapter, we shall survey the research trends and the possible new horizons coming up in Big Data Analytics.作者: 流浪 時間: 2025-3-28 11:43 作者: 搖晃 時間: 2025-3-28 16:39 作者: vitrectomy 時間: 2025-3-28 20:54 作者: dilute 時間: 2025-3-28 23:55
Emerging Research Trends and New Horizons,nce on Data Mining (SDM), IEEE International Conference on Data Engineering (ICDE) and ACM International Conference on Information and Knowledge Management (CIKM). In this chapter, we shall survey the research trends and the possible new horizons coming up in Big Data Analytics.作者: Nucleate 時間: 2025-3-29 04:48
Textbook 2019singly impacting all sectors of business and industry, producing an emerging new information ecosystem. On the applications front, the book offers detailed descriptions of various application areas for Big Data Analytics in the important domains of Social Semantic Web Mining, Banking and Financial S作者: biosphere 時間: 2025-3-29 07:21
https://doi.org/10.1007/978-1-4612-1021-4othesis on the data. Typically, a hypothesis is chosen from a set of candidate patterns assumed in the data. A pattern is taken to be the algorithmic output obtained from transforming the raw input. Thus, machine learning paradigms try to build general patterns from known data to make predictions on unknown data.作者: 蕨類 時間: 2025-3-29 14:24
On Series Which Arise From Products, with machine learning and data mining approaches. Thereby, it allows to study new and old data to make forecasts. Also, providing proactive analytics with predictive modeling helps to convert new and old data into valuable information.作者: 斷斷續(xù)續(xù) 時間: 2025-3-29 17:35
On Series Which Arise From Products, drawing insights. The Big Data phenomenon has resulted in expanding the range of data types that can be processed, enabling the banks and financial institutions to better digest, assimilate and respond in a better way to their physical and digital interactions with the customers.作者: Delectable 時間: 2025-3-29 21:11 作者: 攀登 時間: 2025-3-30 03:23 作者: 一大群 時間: 2025-3-30 07:25
Big Data Analytics for Financial Services and Banking, drawing insights. The Big Data phenomenon has resulted in expanding the range of data types that can be processed, enabling the banks and financial institutions to better digest, assimilate and respond in a better way to their physical and digital interactions with the customers.作者: Baffle 時間: 2025-3-30 11:11
life case studies on successful implementations of Big Data Analytics at large IT companies such as Google, Facebook, LinkedIn and Microsoft. Multi-sectorial case studies on domain-based companies such as Deuts978-981-15-0096-1978-981-15-0094-7作者: Chronological 時間: 2025-3-30 14:04
Big Data Analytics: Systems, Algorithms, Applications作者: LIKEN 時間: 2025-3-30 16:56
Big Data Analytics: Systems, Algorithms, Applications978-981-15-0094-7作者: lesion 時間: 2025-3-30 20:57 作者: 小教堂 時間: 2025-3-31 03:52 作者: exceed 時間: 2025-3-31 06:33
Predictive Modeling for Unstructured Data,n provide myriad applications. Earlier, correlations and patterns in the data are understood with descriptive analytics by compacting data into useful bytes of information. Now, it is no more considered effective to use descriptive analytics as they are responsive. We need to be proactive, and predi作者: TAG 時間: 2025-3-31 12:15 作者: hemoglobin 時間: 2025-3-31 14:46 作者: 排名真古怪 時間: 2025-3-31 18:15
Big Data Analytics in Advertising,ially behaviorally targeted advertisements. Since 2000, the internet became the primary advertising and marketing channel for all the businesses in all sectors. But even then, the click-through rates (CTRs) flattened s after a point of time. CRTs increased 62% in 2013 and much later. Today, brands h作者: 地名詞典 時間: 2025-3-31 23:45 作者: 擔憂 時間: 2025-4-1 02:31
Big Data Analytics and Recommender Systems,oose from a plethora of options. In essence, recommender systems are concerned about predicting personalized item choices for a user. Recommender systems produce a ranked list of items ordered in their order of likeability for the user.作者: 一窩小鳥 時間: 2025-4-1 09:16
Security in Big Data,Web, IOT, Financial Services and Banking, Capital Market and Insurance. In all these cases, the success of such application of the techniques of Big Data Analytics will be critically dependent on security. In this chapter, we shall examine how and to what extent it is possible to insure security in
