標(biāo)題: Titlebook: Big Data Innovations and Applications; 5th International Co Muhammad Younas,Irfan Awan,Salima Benbernou Conference proceedings 2019 Springe [打印本頁] 作者: ACRO 時間: 2025-3-21 18:43
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書目名稱Big Data Innovations and Applications網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Big Data Innovations and Applications被引頻次
書目名稱Big Data Innovations and Applications被引頻次學(xué)科排名
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書目名稱Big Data Innovations and Applications年度引用學(xué)科排名
書目名稱Big Data Innovations and Applications讀者反饋
書目名稱Big Data Innovations and Applications讀者反饋學(xué)科排名
作者: ureter 時間: 2025-3-21 23:16
MapReduce Join Across Geo-Distributed Data Centersning fast and accurate analyses on Big Data. The strength of MapReduce is its capability of exploiting the computing power of a cluster of resources, by distributing the load on multiple computing units, and of scaling with the number of computing units. Today many data analysis algorithms are avail作者: 冷峻 時間: 2025-3-22 00:37
Mobile Device Identification via User Behavior Analysisations utilize the sensing capability of these devices for various purposes, such as human activity recognition, health coaching or advertising, etc. Identifying devices and authenticating unique users is another application area where mobile device sensors can be utilized to ensure more intelligent作者: 極端的正確性 時間: 2025-3-22 05:11 作者: 忍耐 時間: 2025-3-22 12:20
TSWNN+: Check-in Prediction Based on Deep Learning and Factorization Machinensively studied. However, most of the existing research is to predict the next POI for a user. In this paper, we consider a new research problem, which is to predict the number of users visiting the POI during a particular time period. In this work, we extend the TSWNN model structure and propose a 作者: WAIL 時間: 2025-3-22 15:57
Deep Learning Based Sentiment Analysis on Product Reviews on Twitterain opinions or reviews towards a particular entity. The identification of sentiment can be useful for individual decision makers, business organizations and governments. Sentiment analysis is an important research direction. Deep learning is a recent research direction in machine learning, which bu作者: 壟斷 時間: 2025-3-22 17:48 作者: Fatten 時間: 2025-3-22 23:39
Satire Detection in Turkish News Articles: A Machine Learning Approachatforms. Much of the online content contains elements of figurative language, such as, irony, sarcasm and satire. The automatic identification of figurative language can be viewed as a challenging task in natural language processing, where linguistic entities, such as, metaphor, analogy, ambiguity, 作者: CHARM 時間: 2025-3-23 02:20
Committee of the SGTM Neural-Like Structures with Extended Inputs for Predictive Analytics in Insura task’s accuracy. The division of the dataset into segments using dichotomy approach are performed in accordance with the developed algorithm. Both the Kolmogorov-Gabor polynomial and the neural-like structures of the Successive Geometric Transformation Model are proposed for the division and for th作者: habitat 時間: 2025-3-23 07:44 作者: 數(shù)量 時間: 2025-3-23 11:16 作者: incredulity 時間: 2025-3-23 17:04 作者: HILAR 時間: 2025-3-23 19:56
Big Data Analytics for Financial Crime Typologies are based on ML/FT typologies. At the same time, the paper is focused not on the existing methods, but offer its own implemented on the basis of creating various versions of case typologies and further filtering them by the derived criteria. For this purpose, it is supposed to use Big Data tools. T作者: 使出神 時間: 2025-3-23 23:43 作者: 逃避現(xiàn)實(shí) 時間: 2025-3-24 04:08 作者: arbiter 時間: 2025-3-24 08:49
Boundary elements and finite elements,on with the existing ones is established. The main advantages and disadvantages of the proposed method are outlined. The proposed approach can be used to efficiently solve regression and classification tasks for insurance.作者: 南極 時間: 2025-3-24 13:41
Introduction to Brain Topographyork, we present a framework for sharing critical document using IPFS and Blockchain technology. Rather than providing framework specific to a single domain such as electronic health records or legal document sharing, we propose a general framework which can be tailored for the specific domains.作者: 不出名 時間: 2025-3-24 15:26 作者: 牲畜欄 時間: 2025-3-24 21:50 作者: vasculitis 時間: 2025-3-24 23:09 作者: 離開 時間: 2025-3-25 04:13 作者: Anticoagulant 時間: 2025-3-25 09:02 作者: 燒瓶 時間: 2025-3-25 11:38
,Parliament: The House of Commons — II,he successful application of the developed technique is shown on examples of the commission and VAT carousel schemes. To implement and verify this technique a program was written that successfully passed the test on case graphs built on ML/FT typologies.作者: bisphosphonate 時間: 2025-3-25 19:25 作者: G-spot 時間: 2025-3-25 23:20 作者: dearth 時間: 2025-3-26 02:41 作者: Respond 時間: 2025-3-26 05:45
1865-0929 a 2019, held in Istanbul, Turkey, in August 2019..The 15 revised full papers and 1 short paper presented in this volume were carefully reviewed and selected from 48 submissions. The papers are organized in topical sections on advances in big data systems; machine learning and data analytics; big dat作者: STERN 時間: 2025-3-26 12:04
https://doi.org/10.1007/978-3-319-27413-3atabases provide new opportunities by enabling elastic scaling, fault tolerance, high availability and schema flexibility. Despite these benefits, their limitations in the flexibility of query mechanisms impose a real barrier for any application that has not predetermined access use-cases. One of th作者: 補(bǔ)充 時間: 2025-3-26 15:48 作者: avenge 時間: 2025-3-26 18:11 作者: LINE 時間: 2025-3-26 21:08 作者: NOMAD 時間: 2025-3-27 04:30 作者: 中古 時間: 2025-3-27 07:31
Introduction to Black Hole Astrophysicsain opinions or reviews towards a particular entity. The identification of sentiment can be useful for individual decision makers, business organizations and governments. Sentiment analysis is an important research direction. Deep learning is a recent research direction in machine learning, which bu作者: 豐滿中國 時間: 2025-3-27 11:26 作者: alliance 時間: 2025-3-27 16:30 作者: Directed 時間: 2025-3-27 18:55 作者: medium 時間: 2025-3-28 00:23 作者: FLIC 時間: 2025-3-28 03:39 作者: 一條卷發(fā) 時間: 2025-3-28 07:24 作者: 熱烈的歡迎 時間: 2025-3-28 11:09 作者: 率直 時間: 2025-3-28 18:16
Buddhist Wisdom and Defining Principlestructure engineering system. The monitoring system is based on the concept of edge computing - cloud computing and is designed to collect and analyze Big data procured via the Industrial Internet of Things (IIoT). Author acknowledges support from the MEPhI Academic Excellence Project (Contract No. 0作者: Foreknowledge 時間: 2025-3-28 19:32 作者: 沙草紙 時間: 2025-3-29 02:39
978-3-030-27354-5Springer Nature Switzerland AG 2019作者: 闡釋 時間: 2025-3-29 06:58
Communications in Computer and Information Sciencehttp://image.papertrans.cn/b/image/185644.jpg作者: heterodox 時間: 2025-3-29 08:07 作者: 躲債 時間: 2025-3-29 15:16
Buddhist Wisdom and Defining Principlestructure engineering system. The monitoring system is based on the concept of edge computing - cloud computing and is designed to collect and analyze Big data procured via the Industrial Internet of Things (IIoT). Author acknowledges support from the MEPhI Academic Excellence Project (Contract No. 02.a03.21.0005).作者: 財主 時間: 2025-3-29 18:56
Monitoring System for the Housing and Utility Services Based on the Digital Technologies IIoT, Big Dtructure engineering system. The monitoring system is based on the concept of edge computing - cloud computing and is designed to collect and analyze Big data procured via the Industrial Internet of Things (IIoT). Author acknowledges support from the MEPhI Academic Excellence Project (Contract No. 02.a03.21.0005).作者: Aphorism 時間: 2025-3-29 19:47 作者: tooth-decay 時間: 2025-3-30 00:38 作者: arrogant 時間: 2025-3-30 04:36 作者: Respond 時間: 2025-3-30 09:26
MapReduce Join Across Geo-Distributed Data Centers, in such scenarios the cost for moving data among nodes connected via geographic links counterbalances the benefit of parallelization. In this paper the issues of running MapReduce Joins in a geo-distributed computing context are discussed. Furthermore, we propose to boost the performance of the Jo作者: 寄生蟲 時間: 2025-3-30 16:10
Mobile Device Identification via User Behavior Analysisr than 25 GB, which consists of accelerometer and gyroscope sensor data from 21 distinct devices is utilized. We employ different classification methods on extracted 40 features based on various time windows from mobile sensors. Namely, we use random forest, gradient boosting machine, and generalize作者: Blemish 時間: 2025-3-30 17:46 作者: 平項(xiàng)山 時間: 2025-3-30 21:24
Deep Learning Based Sentiment Analysis on Product Reviews on Twitterd convolutional neural network (CNN) have been utilized. In the empirical analysis, different subsets of Twitter messages, ranging from 5000 to 50.000 are taken into consideration. The prediction results obtained by deep-learning based schemes have been compared to conventional classifiers (such as,作者: 完整 時間: 2025-3-31 03:17
A Cluster-Based Machine Learning Model for Large Healthcare Data Analysisired output, which is Expanded Prostate Index Composite-26 (EPIC-26) domain scores. EPIC-26 is being used for assessing a range of HRQOL issues related to the diagnosis and treatment of prostate cancer. Different feature extraction methods are applied to extract features and the best method is the p作者: 預(yù)知 時間: 2025-3-31 05:16 作者: Ophthalmologist 時間: 2025-3-31 12:32
The Information System for the Research in Carotid Atherosclerosiscreate a decision-making expert information system which should help decide about risk assessment in atherosclerosis of carotid artery. The idea of the system is based on differentiation of echogenicity grade according to Echo-Index value. In consequence, the system should classify the plaques into 作者: 異端 時間: 2025-3-31 16:55
