A systematic data characteristic understanding framework towards physical-sensor big data challenges | Paper Citation Record

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This paper cites Challenges of big data analysis.

A systematic data characteristic understanding framework towards physical-sensor big data challenges Challenges of big data analysis

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This paper cites Fair data enabling new horizons for materials research.

A systematic data characteristic understanding framework towards physical-sensor big data challenges Fair data enabling new horizons for materials research

Reference 2

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This paper cites Uncertainty in big data analytics: Survey, opportunities, and challenges.

A systematic data characteristic understanding framework towards physical-sensor big data challenges Uncertainty in big data analytics: Survey, opportunities, and challenges

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This paper cites https://www.statista.com/statistics/871513/worldwide-data-created/.

A systematic data characteristic understanding framework towards physical-sensor big data challenges https://www.statista.com/statistics/871513/worldwide-data-created/

Reference 4

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This paper cites Big data for healthcare industry 4.0: Applications, challenges and future perspectives.

A systematic data characteristic understanding framework towards physical-sensor big data challenges Big data for healthcare industry 4.0: Applications, challenges and future perspectives

Reference 5

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This paper cites Beyond the hype: Big data concepts, methods, and analytics.

A systematic data characteristic understanding framework towards physical-sensor big data challenges Beyond the hype: Big data concepts, methods, and analytics

Reference 6

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This paper cites Big data quality framework: A holistic approach to continuous quality management.

A systematic data characteristic understanding framework towards physical-sensor big data challenges Big data quality framework: A holistic approach to continuous quality management

Reference 7

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This paper cites A novel rigorous measurement model for big data quality characteristics.

A systematic data characteristic understanding framework towards physical-sensor big data challenges A novel rigorous measurement model for big data quality characteristics

Reference 8

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This paper cites Trends and future perspective challenges in big data.

A systematic data characteristic understanding framework towards physical-sensor big data challenges Trends and future perspective challenges in big data

Reference 9

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A systematic data characteristic understanding framework towards physical-sensor big data challenges big data

Reference 10

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A systematic data characteristic understanding framework towards physical-sensor big data challenges 3D data management: Controlling data volume, velocity and variety

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This paper cites A zero emission neighbourhoods data management architecture for smart city scenarios: Discussions toward 6vs challenges.

A systematic data characteristic understanding framework towards physical-sensor big data challenges A zero emission neighbourhoods data management architecture for smart city scenarios: Discussions toward 6vs challenges

Reference 12

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This paper cites A model for unpacking big data analytics in high -frequency trading.

A systematic data characteristic understanding framework towards physical-sensor big data challenges A model for unpacking big data analytics in high -frequency trading

Reference 13

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This paper cites A comprehensive scenario agnostic data lifecycle model for an eﬃcient data complexity management.

A systematic data characteristic understanding framework towards physical-sensor big data challenges A comprehensive scenario agnostic data lifecycle model for an eﬃcient data complexity management

Reference 14

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A systematic data characteristic understanding framework towards physical-sensor big data challenges Toward a novel measurement framework for big data (mega)

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A systematic data characteristic understanding framework towards physical-sensor big data challenges Seven v's of big data understanding big data to extract value

Reference 16

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This paper cites A study of big data analytics using apache spark with python and scala.

A systematic data characteristic understanding framework towards physical-sensor big data challenges A study of big data analytics using apache spark with python and scala

Reference 17

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This paper cites Recent quality models in bigdata applications.

A systematic data characteristic understanding framework towards physical-sensor big data challenges Recent quality models in bigdata applications

Reference 18

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A systematic data characteristic understanding framework towards physical-sensor big data challenges Deﬁning big data

Reference 19

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This paper cites Towards a comprehensive data lifecycle model for big data environments.

A systematic data characteristic understanding framework towards physical-sensor big data challenges Towards a comprehensive data lifecycle model for big data environments

Reference 20

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This paper cites Understanding the impact of big data on ﬁrm performance: The necessity of conceptually diﬀerentiating among big data characteristics.

A systematic data characteristic understanding framework towards physical-sensor big data challenges Understanding the impact of big data on ﬁrm performance: The necessity of conceptually diﬀerentiating among big data characteristics

Reference 21

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This paper cites A global manufacturing big data ecosystem for fault detection in predictive maintenance.

A systematic data characteristic understanding framework towards physical-sensor big data challenges A global manufacturing big data ecosystem for fault detection in predictive maintenance

Reference 22

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A systematic data characteristic understanding framework towards physical-sensor big data challenges Big data perspective for driver/driving behavior

Reference 23

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A systematic data characteristic understanding framework towards physical-sensor big data challenges A trustworthy privacy preserving framework for machine learning in industrial IoT systems

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A systematic data characteristic understanding framework towards physical-sensor big data challenges Mu l ti-sensor information fusion based on machine learning for real applications in human activity recognition: State -of-the-art and research challenges

Reference 25

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A systematic data characteristic understanding framework towards physical-sensor big data challenges Internet of things in industries: A survey

Reference 26

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A systematic data characteristic understanding framework towards physical-sensor big data challenges Industry 4.0: A survey on technologies, applications and open research issues

Reference 27

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A systematic data characteristic understanding framework towards physical-sensor big data challenges Privacy-aware traﬃc ﬂow prediction based on multi-party sensor data with zero trust in smart city

Reference 28

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A systematic data characteristic understanding framework towards physical-sensor big data challenges Serverless data pipeline approaches for IoT data in fog and cloud computing

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A systematic data characteristic understanding framework towards physical-sensor big data challenges Unresolved cited work

Reference 30

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A systematic data characteristic understanding framework towards physical-sensor big data challenges Human activity recognition in artiﬁcial intelligence framework: A narrative review

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A systematic data characteristic understanding framework towards physical-sensor big data challenges Dalif: A data lifecycle framework for data-driven governments

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A systematic data characteristic understanding framework towards physical-sensor big data challenges Big-data approaches lead to an increased understanding of the ecology of animal movement

Reference 33

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A systematic data characteristic understanding framework towards physical-sensor big data challenges Big data for creating and capturing value in the digitalized environment: Unpacking the eﬀects of volume, variety, and veracity on ﬁrm performance

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A systematic data characteristic understanding framework towards physical-sensor big data challenges A model of the data (life) cycles with application to quality

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A systematic data characteristic understanding framework towards physical-sensor big data challenges Reference architecture and classiﬁcation of technologies, products and services for big data systems

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A systematic data characteristic understanding framework towards physical-sensor big data challenges Toward data mining engineering: A software engineering approach

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This paper cites CRISP-DM twenty years later: From data mining processes to data science trajectories.

A systematic data characteristic understanding framework towards physical-sensor big data challenges CRISP-DM twenty years later: From data mining processes to data science trajectories

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A systematic data characteristic understanding framework towards physical-sensor big data challenges C RISP-DM: Towards a standard process model for data mining

Reference 39

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A systematic data characteristic understanding framework towards physical-sensor big data challenges APREP-DM: A framework for automating the pre-processing of a sensor data analysis based on CRISP-DM

Reference 40

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A systematic data characteristic understanding framework towards physical-sensor big data challenges Variations of length of stay: A case study using control charts in the CRISP-DM framework

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A systematic data characteristic understanding framework towards physical-sensor big data challenges C RISP data mining methodology extension for medical domain

Reference 42

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A systematic data characteristic understanding framework towards physical-sensor big data challenges Evaluating frameworks for implementing machine learning in signal processing: A comparative study of CRISP-DM, SEMMA and KDD

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A systematic data characteristic understanding framework towards physical-sensor big data challenges Synthesizing CRISP-DM and quality management: A data mining approach for production processes

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This paper cites On applicability of big data analytics in the closed -loop product lifecycle: Integration of crisp-dm standard.

A systematic data characteristic understanding framework towards physical-sensor big data challenges On applicability of big data analytics in the closed -loop product lifecycle: Integration of crisp-dm standard

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This paper cites Addressing big data issues in scientiﬁc data infrastructure.

A systematic data characteristic understanding framework towards physical-sensor big data challenges Addressing big data issues in scientiﬁc data infrastructure

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This paper cites A comprehensive survey on feature selection in the various ﬁelds of machine learning.

A systematic data characteristic understanding framework towards physical-sensor big data challenges A comprehensive survey on feature selection in the various ﬁelds of machine learning

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A systematic data characteristic understanding framework towards physical-sensor big data challenges Feature dimensionality reduction: A review

Reference 49

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This paper cites Use of large-scale hrqol datasets to generate individualised predictions and inform patients about the likely beneﬁt of surgery.

A systematic data characteristic understanding framework towards physical-sensor big data challenges Use of large-scale hrqol datasets to generate individualised predictions and inform patients about the likely beneﬁt of surgery

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This paper cites A review of industrial big data for decision making in intelligent manufacturing.

A systematic data characteristic understanding framework towards physical-sensor big data challenges A review of industrial big data for decision making in intelligent manufacturing

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This paper cites Combining structured and unstructured data for predictive models: A deep learning approach.

A systematic data characteristic understanding framework towards physical-sensor big data challenges Combining structured and unstructured data for predictive models: A deep learning approach

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This paper cites Knowledge discovery in heterogeneous and unstructured data of industry 4.0 systems: Challenges and approaches.

A systematic data characteristic understanding framework towards physical-sensor big data challenges Knowledge discovery in heterogeneous and unstructured data of industry 4.0 systems: Challenges and approaches

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This paper cites Big data analytics in oil and gas industry: An emerging trend.

A systematic data characteristic understanding framework towards physical-sensor big data challenges Big data analytics in oil and gas industry: An emerging trend

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A systematic data characteristic understanding framework towards physical-sensor big data challenges Data integration for large - scale models of species distributions

Reference 55

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A systematic data characteristic understanding framework towards physical-sensor big data challenges The use of big data analytics in healthcare

Reference 56

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A systematic data characteristic understanding framework towards physical-sensor big data challenges Sice: An improved missing data imputation technique

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A systematic data characteristic understanding framework towards physical-sensor big data challenges Generative adversarial networks for imputing missing data for big data clinical research

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A systematic data characteristic understanding framework towards physical-sensor big data challenges Statistical analysis with missing data: John Wiley & Sons; 2019

Reference 62

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Reference 63

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A systematic data characteristic understanding framework towards physical-sensor big data challenges Fundamentals of machine learning for predictive data analytics: Algorithms, worked examples, and case studies: MIT press; 2020

Reference 64

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A systematic data characteristic understanding framework towards physical-sensor big data challenges Characteristic-based clustering for time series data

Reference 65

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A systematic data characteristic understanding framework towards physical-sensor big data challenges Gratis: Generating time series with diverse and controllable characteristics

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A systematic data characteristic understanding framework towards physical-sensor big data challenges A review on outlier/anomaly detection in time series data

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A systematic data characteristic understanding framework towards physical-sensor big data challenges Anomaly detection in time series: A comprehensive evaluation

Reference 68

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A systematic data characteristic understanding framework towards physical-sensor big data challenges Understanding and using time series analyses in addiction research

Reference 69

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A systematic data characteristic understanding framework towards physical-sensor big data challenges Framework and modelling of inclusive manufacturing system

Reference 70

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A systematic data characteristic understanding framework towards physical-sensor big data challenges Challenges and trends of big data analytics

Reference 71

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A systematic data characteristic understanding framework towards physical-sensor big data challenges Initiating predictive maintenance for a conveyor motor in a bottling plant using industry 4.0 concepts

Reference 72

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A systematic data characteristic understanding framework towards physical-sensor big data challenges Intelligent predictive maintenance for fault diagnosis and prognosis in machine centers: Industry 4.0 scenario

Reference 73

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A systematic data characteristic understanding framework towards physical-sensor big data challenges Multiple Instance-Based Video Anomaly Detection using Deep Temporal Encoding-Decoding

Reference 74

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A systematic data characteristic understanding framework towards physical-sensor big data challenges Missing value imputation in multivariate time series with end-to-end generative adversarial networks

Reference 75

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A systematic data characteristic understanding framework towards physical-sensor big data challenges A novel hybrid feature importance and feature interaction detection framework for predictive optimization in industry 4.0 applications

Reference 76

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A systematic data characteristic understanding framework towards physical-sensor big data challenges A data-driven two-phase multi-split causal ensemble model for time series

Reference 77

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A systematic data characteristic understanding framework towards physical-sensor big data challenges Statsmodels: Econometric and statistical modeling with python

Reference 78

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Reference 93

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