Big Data: A Survey

MapReduce: simplified data processing on large clusters

Dean, J., & Ghemawat, S. (2008) · Communications of the ACM · doi:10.1145/1327452.1327492 · Cited by 18,476

The anatomy of a large-scale hypertextual Web search engine

Brin, S., & Page, L. (1998) · Computer Networks and ISDN Systems · doi:10.1016/s0169-7552(98)00110-x · Cited by 16,004

An index to quantify an individual’s scientific research output

Hirsch, J. E. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0507655102 · Cited by 11,669

Foundations of statistical natural language processing

Manning, C. D., & Schütze, H. (1999) · Cited by 9,816

An Introduction to Multivariate Statistical Analysis

Muirhead, R. J., & Anderson, T. W. (1986) · Journal of Business and Economic Statistics · doi:10.2307/1391399 · Cited by 9,179

Top 10 algorithms in data mining

Wu, X., Kumar, V., Ross Quinlan, J., Ghosh, J., Yang, Q., Motoda, H., McLachlan, G. J., Ng, A., Liu, B., Yu, P. S., et al. (2008) · Knowledge and Information Systems · doi:10.1007/s10115-007-0114-2 · Cited by 5,667

Untitled work

(2011) · Cited by 5,203

Detecting influenza epidemics using search engine query data

Ginsberg, J., Mohebbi, M. H., Patel, R. S., Brammer, L., Smolinski, M. S., & Brilliant, L. (2009) · Nature · doi:10.1038/nature07634 · Cited by 4,295

Big data: a revolution that will transform how we live, work, and think

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Resilient distributed datasets: a fault-tolerant abstraction for in-memory cluster computing

Zaharia, M., Chowdhury, M., Das, T., Dave, A., Ma, J. H., McCauley, M., Franklin, M. J. M., Shenker, S. J., & Stoica, I. G. (2012) · Cited by 3,622

Big data and rule-based recommendation system in Internet of Things

Jeong, H., Park, B., Park, M.-W., Kim, K., & Choi, K. (2017) · Cluster Computing · doi:10.1007/s10586-017-1078-y · Cited by 22

SensorCentral: A Research Oriented, Device Agnostic, Sensor Data Platform

Rafferty, J., Synnott, J., Ennis, A., Nugent, C., McChesney, I., & Cleland, I. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-67585-5_11 · Cited by 22

Data in the time of COVID-19: a general methodology to select and secure a NoSQL DBMS for medical data

ElDahshan, K. A., AlHabshy, A. A., & Abutaleb, G. (2020) · PeerJ Computer Science · doi:10.7717/peerj-cs.297 · Cited by 22

Securing IoT-based healthcare systems from counterfeit medicine penetration using Blockchain

Preetha, A. D., & Kumar, T. S. P. (2021) · Applied Nanoscience · doi:10.1007/s13204-021-01984-4 · Cited by 23

Spatiotemporal grid-based crash prediction—application of a transparent deep hybrid modeling framework

Kashifi, M. T., Alsghan, I., Rahman, S. M., & Al-Ahmadi, H. M. (2022) · Neural Computing and Applications · doi:10.1007/s00521-022-07511-y · Cited by 23

Effective Data Utilization in the Context of Industry 4.0 Technology Integration

Janík, S., Szabó, P., Mĺkva, M., & Mareček-Kolibiský, M. (2022) · Applied Sciences · doi:10.3390/app122010517 · Cited by 22

What Is (Not) Big Data Based on Its 7Vs Challenges: A Survey

García, C. G., & Álvarez-Fernández, E. (2022) · Big Data and Cognitive Computing · doi:10.3390/bdcc6040158 · Cited by 27

Automated and intelligent systems for next-generation-based smart applications

Deekshetha, H. R., & Tyagi, A. K. (2023) · Elsevier eBooks · doi:10.1016/b978-0-323-98352-5.00019-7 · Cited by 22

An iterative methodology for big data management, analysis and visualization

Tardío, R., Maté, A., & Trujillo, J. C. (2015) · IEEE International Conference on Big Data (BigData) · doi:10.1109/bigdata.2015.7363798 · Cited by 22

Design and Construction of a Big Data Analytics Framework for Health Applications

Kuo, M.-H., Chrimes, D., Moa, B., & Hu, W. P. (2015) · IEEE International Conference on Smart City/SocialCom/SustainCom · doi:10.1109/smartcity.2015.140 · Cited by 22

Innovation Capability, Knowledge Management and Big Data Technology: A Maritime Business Case

Lambrou, M. (2016) · International Journal of Advanced Corporate Learning (iJAC) · doi:10.3991/ijac.v9i2.6010 · Cited by 22

Combining customer needs and the customer’s way of using the product to set customer-focused targets in the House of Quality

Bigorra, A. M., & Isaksson, O. (2016) · International Journal of Production Research · doi:10.1080/00207543.2016.1238114 · Cited by 22

Towards Large-Scale, Heterogeneous Anomaly Detection Systems in Industrial Networks: A Survey of Current Trends

Iturbe, M., Garitano, I., Zurutuza, U., & Uribeetxeberria, R. (2017) · Security and Communication Networks · doi:10.1155/2017/9150965 · Cited by 22

A Scalable, Research Oriented, Generic, Sensor Data Platform

Rafferty, J., Synnott, J., Nugent, C., Ennis, A., Catherwood, P. A., McChesney, I., Cleland, I., & McClean, S. I. (2018) · IEEE Access · doi:10.1109/access.2018.2852656 · Cited by 22

Big Data Security and Privacy Concerns: A Review

Khanan, A., Abdullah, S., Mohamed, A. H. H. M., Mehmood, A., & Ariffin, K. A. Z. (2019) · Advances in Science, Technology & Innovation/Advances in science, technology & innovation · doi:10.1007/978-3-030-01659-3_8 · Cited by 22

Cloud-based big data analytics platform using algorithm templates for the manufacturing industry

Jun, C., Lee, J. Y., & Kim, B. H. (2019) · International Journal of Computer Integrated Manufacturing · doi:10.1080/0951192x.2019.1610578 · Cited by 22

Digitalization of Business Functions under Industry 4.0

CAGLE, M. N., Yılmaz, K., & Dogru-Dastan, H. (2019) · Contributions to management science · doi:10.1007/978-3-030-29739-8_6 · Cited by 22

Bibliometric and Visualized Analysis of China's Smart Grid Research 2008–2018

Wang, C., Lv, T., & Deng, X. (2020) · Frontiers in Research Metrics and Analytics · doi:10.3389/frma.2020.551147 · Cited by 24

The Full Knowledge of Big Data in the Integration of Inter-Organizational Information

Poleto, T., de Carvalho, V. D. H., & Costa, A. P. C. S. (2016) · International Journal of Decision Support System Technology · doi:10.4018/ijdsst.2017010102 · Cited by 22

Interpretative identification of the faulty conditions in a cyclic manufacturing process

Kozjek, D., Vrabič, R., Kralj, D., & Butala, P. (2017) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2017.03.001 · Cited by 22

Vessel Trajectory Data Mining: A Review

Troupiotis-Kapeliaris, A., Kastrisios, C., & Zissis, D. (2025) · IEEE Access · doi:10.1109/access.2025.3525952 · Cited by 21

Towards the evaluation of a big data-as-a-service model: A decision theoretic approach

Skourletopoulos, G., Mavromoustakis, C. X., Chatzimisios, P., Mastorakis, G. N., Pallis, E., & Batalla, J. M. (2016) · IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) · doi:10.1109/infcomw.2016.7562202 · Cited by 21

Choosing the Best Algorithm for an Incremental On-line Learning Task

Losing, V., Hammer, B., & Wersing, H. (2016) · Publikationen an der Universität Bielefeld (Universität Bielefeld) · Cited by 21

FOGG: A Fog Computing Based Gateway to Integrate Sensor Networks to Internet

Adhatarao, S. S., Arumaithurai, M., & Fu, X. (2017) · International Teletraffic Congress · doi:10.23919/itc.2017.8065709 · Cited by 21

Team Recognition in Big Scholarly Data: Exploring Collaboration Intensity

Yu, S., Xia, F., Zhang, K., Ning, Z., Zhong, J., & Chengfei Liu, A. (2017) · IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech) · doi:10.1109/dasc-picom-datacom-cyberscitec.2017.155 · Cited by 21

ZAKI+: A Machine Learning Based Process Mapping Tool for SpMV Computations on Distributed Memory Architectures

Usman, S., Mehmood, R., Katib, I. A., & Albeshri, A. A. (2019) · IEEE Access · doi:10.1109/access.2019.2923565 · Cited by 21

A scalable and effective rough set theory-based approach for big data pre-processing

Dagdia, Z. C., Zarges, C., Beck, G., & Lebbah, M. (2020) · Knowledge and Information Systems · doi:10.1007/s10115-020-01467-y · Cited by 21

Development of Novel Big Data Analytics Framework for Smart Clothing

Ahsan, M., Teay, S. H., & Albarbar, A. (2020) · IEEE Access · doi:10.1109/access.2020.3015152 · Cited by 22

TVD-MRDL: traffic violation detection system using MapReduce-based deep learning for large-scale data

Asadianfam, S., Shamsi, M., & Kenari, A. R. (2020) · Multimedia Tools and Applications · doi:10.1007/s11042-020-09714-8 · Cited by 21

A study of micromanufacturing process fingerprints in micro-injection moulding for machine learning and Industry 4.0 applications

Gülçür, M., & Whiteside, B. (2021) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-021-07252-7 · Cited by 21

Reputational Risk Associated with Big Data Research and Development: An Interdisciplinary Perspective

Stitzlein, C. A., Fielke, S., Waldner, F., & Sanderson, T. (2021) · Sustainability · doi:10.3390/su13169280 · Cited by 21

Machine Learning Algorithms Used in PSE Environments: A Didactic Approach and Critical Perspective

Fuentes‐Cortés, L. F., Flores‐Tlacuahuac, A., & Nigam, K. D. P. (2022) · Industrial & Engineering Chemistry Research · doi:10.1021/acs.iecr.2c00335 · Cited by 21

Metaheuristic Based Clustering with Deep Learning Model for Big Data Classification

Krishnaswamy, R., Subramaniam, K., Nandini, V., Vijayalakshmi, K., Kadry, S., & Nam, Y. (2022) · Computer Systems Science and Engineering · doi:10.32604/csse.2023.024901 · Cited by 21

Discovering Urban Governance Parameters for Online Learning in Saudi Arabia During COVID-19 Using Topic Modeling of Twitter Data

Alswedani, S., Katib, I. A., Abozinadah, E., & Mehmood, R. (2022) · Frontiers in Sustainable Cities · doi:10.3389/frsc.2022.751681 · Cited by 21

Data Integration in Big Data Environment

Arputhamary, B., & Arockiam, L. (2015) · Bonfring International Journal of Data Mining · doi:10.9756/bijdm.8001 · Cited by 21

Measurable Security, Privacy and Dependability in Smart Grids

Noll, J., Garitano, I., Fayyad, S., Åsberg, E., & Abie, H. (2015) · Journal of Cyber Security and Mobility · doi:10.13052/jcsm2245-1439.342 · Cited by 21

A Mathematical Foundation of Big Data

Sun, Z., & Wang, P. P. (2017) · New Mathematics and Natural Computation · doi:10.1142/s1793005717400014 · Cited by 21

A Data-Driven Holistic Approach to Fault Prognostics in a Cyclic Manufacturing Process

Kozjek, D., Vrabič, R., Kralj, D., & Butala, P. (2017) · Procedia CIRP · doi:10.1016/j.procir.2017.03.109 · Cited by 21

Semantic interoperability and pattern classification for a service-oriented architecture in pregnancy care

Moreira, M. W. L., Rodrigues, J. J. P. C., Sangaiah, A. K., Al-Muhtadi, J. F., & Korotaev, V. V. (2018) · Future Generation Computer Systems · doi:10.1016/j.future.2018.04.031 · Cited by 21

Defining, enforcing and checking privacy policies in data-intensive applications

Guerriero, M., Tamburri, D. A., & Nitto, E. D. (2018) · International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS) · doi:10.1145/3194133.3194140 · Cited by 21

Towards a more reliable and scalable architecture for smart home environments

Plantevin, V., Bouzouane, A., Bouchard, B., & Gaboury, S. (2018) · Journal of Ambient Intelligence and Humanized Computing · doi:10.1007/s12652-018-0954-5 · Cited by 21

BigDataSDNSim: A simulator for analyzing big data applications in software‐defined cloud data centers

Alwasel, K., Calheiros, R. N., Garg, S., Buyya, R., Pathan, M., Georgakopoulos, D., & Ranjan, R. (2020) · Software Practice and Experience · doi:10.1002/spe.2917 · Cited by 21

Short-Term Load Forecasting with LSTM Based Ensemble Learning

Wang, L., Mao, S., & Wilamowski, B. M. (2019) · IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData) · doi:10.1109/ithings/greencom/cpscom/smartdata.2019.00145 · Cited by 20

Discussing Relations Between Dynamic Business Environments and Big Data Analytics

Staegemann, D. G., Volk, M., Daase, C., & Turowski, K. (2020) · Complex Systems Informatics and Modeling Quarterly · doi:10.7250/csimq.2020-23.05 · Cited by 21

Smart City Development: ICT Innovation for Urban Sustainability

Mora, L., Deakin, M., Aina, Y. A., & Appio, F. P. (2019) · Encyclopedia of the UN sustainable development goals · doi:10.1007/978-3-319-71061-7_27-2 · Cited by 21

Data Quality Management in Big Data: Strategies, Tools, and Educational Implications

Nguyen, T., Nguyen, H.-T., & Nguyen-Hoang, T.-A. (2025) · Journal of Parallel and Distributed Computing · doi:10.1016/j.jpdc.2025.105067 · Cited by 20

Omics big data for crop improvement: Opportunities and challenges

Vasupalli, N., Bhat, J. A., Jain, P., Sri, T., Islam, M. A., Shivaraj, S. M., Singh, S. K., Deshmukh, R., Sonah, H., & Lin, X. (2024) · The Crop Journal · doi:10.1016/j.cj.2024.10.007 · Cited by 21

Recent developments in data mining applications and techniques

Almasoud, A. M., Al-Khalifa, H. S., & Al‐Salman, A. S. (2015) · International Conference on Digital Information Management · doi:10.1109/icdim.2015.7381867 · Cited by 20

A distributed rough set theory based algorithm for an efficient big data pre-processing under the spark framework

Dagdia, Z. C., Zarges, C., Beck, G., & Lebbah, M. (2017) · IEEE International Conference on Big Data (BigData) · doi:10.1109/bigdata.2017.8258008 · Cited by 20

Big data security and privacy issues — A survey

Joshi, N., & Kadhiwala, B. (2017) · Innovations in Power and Advanced Computing Technologies (i-PACT) · doi:10.1109/ipact.2017.8245064 · Cited by 20

Evaluating Several Design Patterns and Trends in Big Data Warehousing Systems

Costa, C., & Santos, M. Y. (2018) · Lecture notes in computer science · doi:10.1007/978-3-319-91563-0_28 · Cited by 20

Exploring a Big Data Approach to Building a List Frame for Urban Agriculture: A Pilot Study in the City of Baltimore

Young, L. J., Hyman, M., & Rater, B. R. (2018) · Journal of Official Statistics · doi:10.2478/jos-2018-0015 · Cited by 22

Application of Cloud Computing and Internet of Things to Improve Supply Chain Processes

Suguna, S. K., & Kumar, S. N. (2018) · EAI/Springer Innovations in Communication and Computing · doi:10.1007/978-3-319-99061-3_9 · Cited by 20

TOP-Storm: A topology-based resource-aware scheduler for Stream Processing Engine

Muhammad, A., Aleem, M., & Islam, M. A. (2020) · Cluster Computing · doi:10.1007/s10586-020-03117-y · Cited by 20

Big Data Provision for Digital Twins in Industry 4.0 Logistics Processes

Figueiras, P. A., Lourenço, L., Costa, R., Graça, D., García, G., & Jardim‐Gonçalves, R. (2021) · IEEE International Workshop on Metrology for Industry 4.0 & IoT (MetroInd4.0&IoT) · doi:10.1109/metroind4.0iot51437.2021.9488507 · Cited by 20

Replica selection and placement techniques on the IoT and edge computing: a deep study

Shao, Z.-L., Huang, C., & Li, H. (2021) · Wireless Networks · doi:10.1007/s11276-021-02793-x · Cited by 20

How does cloud computing help businesses to manage big data issues

Latifian, A. (2022) · Kybernetes · doi:10.1108/k-05-2021-0432 · Cited by 20

Role of Agents to Enhance the Security and Scalability in Cloud Environment

Malhotra, M., & Singh, A. S. (2019) · IGI Global eBooks · doi:10.4018/978-1-5225-8176-5.ch028 · Cited by 20

Assessing veracity of big data: An in-depth evaluation process from the comparison of Mobile phone traces and groundtruth data in traffic monitoring

Nalin, A., Vignali, V., Lantieri, C., Cappellari, D., Zamengo, B., & Simone, A. (2024) · Journal of Transport Geography · doi:10.1016/j.jtrangeo.2024.103930 · Cited by 20

A review of big data environment and its related technologies

Mohammed, A. F., Humbe, V. T., & Chowhan, S. S. (2016) · International Conference on Information Communication and Embedded Systems · doi:10.1109/icices.2016.7518904 · Cited by 20

City digital pulse: a cloud based heterogeneous data analysis platform

Li, Z., Zhu, S., Hong, H., Li, Y., & Saddik, A. E. (2016) · Multimedia Tools and Applications · doi:10.1007/s11042-016-4038-2 · Cited by 20

SLA-based profit optimization for resource management of big data analytics-as-a-service platforms in cloud computing environments

Zhao, Y., Calheiros, R. N., Bailey, J., & Sinnott, R. (2016) · IEEE International Conference on Big Data (BigData) · doi:10.1109/bigdata.2016.7840634 · Cited by 20

A fuzzy comprehensive evaluation algorithm for analyzing electronic word-of-mouth

Li, N., Tung, V. W. S., & Law, R. (2017) · Asia Pacific Journal of Tourism Research · doi:10.1080/10941665.2017.1308395 · Cited by 20

Dynamic resource allocation for big data streams based on data characteristics (5 V s)

Kaur, N., & Sood, S. K. (2017) · International Journal of Network Management · doi:10.1002/nem.1978 · Cited by 20

Big data y cirugía: la revolución digital continúa

Targarona, E. M., Balla, A., & Rodríguez, G. B. (2017) · Cirugía Española · doi:10.1016/j.ciresp.2017.07.009 · Cited by 20

Multi-level semantic annotation and unified data integration using semantic web ontology in big data processing

Rani, P. S., Suresh, R. M., & Sethukarasi, R. (2017) · Cluster Computing · doi:10.1007/s10586-017-1029-7 · Cited by 20

Structure and patterns of cross-national Big Data research collaborations

Hu, J., & Zhang, Y. (2017) · Journal of Documentation · doi:10.1108/jd-12-2016-0146 · Cited by 20

Big Data Analytics for Intelligent Internet of Things

Ahmed, M., Choudhury, S., & Al‐Turjman, F. (2019) · Transactions on computational science and computational intelligence · doi:10.1007/978-3-030-04110-6_6 · Cited by 20

Dynamic Big-Data Broadcast in Fat-Tree Data Center Networks With Mobile IoT Devices

Misra, S., Mondal, A., & Khajjayam, S. (2019) · IEEE Systems Journal · doi:10.1109/jsyst.2019.2899754 · Cited by 20

ZAKI: A Smart Method and Tool for Automatic Performance Optimization of Parallel SpMV Computations on Distributed Memory Machines

Usman, S., Mehmood, R., Katib, I. A., Albeshri, A. A., & Altowaijri, S. M. (2019) · Mobile Networks and Applications · doi:10.1007/s11036-019-01318-3 · Cited by 20

Query is GAN: Scene Retrieval With Attentional Text-to-Image Generative Adversarial Network

Yanagi, R., Togo, R., Ogawa, T., & Haseyama, M. (2019) · IEEE Access · doi:10.1109/access.2019.2947409 · Cited by 22

Social media analytics in the construction industry comparison study between China and the United States

Tang, L. M., Griffith, L., Stevens, M., & Hardie, M. (2020) · Engineering Construction & Architectural Management · doi:10.1108/ecam-12-2019-0717 · Cited by 20

Big Data and Cloud Computing

Gautam, A., & Chatterjee, I. (2020) · International Journal of Operations Research and Information Systems · doi:10.4018/ijoris.2020070102 · Cited by 23

A Scalable Heterogeneous Big Data Framework for e-Learning Systems

Otoo-Arthur, D., & van Zyl, T. L. (2020) · International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems (icABCD) · doi:10.1109/icabcd49160.2020.9183863 · Cited by 20

A Framework for Ensuring the Quality of a Big Data Service

Ding, J., Zhang, D., & Hu, X. (2016) · IEEE International Conference on Services Computing · doi:10.1109/scc.2016.18 · Cited by 20

Big data in telecommunication operators: data, platform and practices

Wang, Z., Wei, G., Zhan, Y., & Sun, Y. (2017) · Journal of Communications and Information Networks · doi:10.1007/s41650-017-0010-1 · Cited by 20

IHEMHA: Interactive healthcare system design with emotion computing and medical history analysis

Ullah, M. R., Bhuiyan, M. A. R., & Das, A. K. (2017) · International Conference on Informatics, Electronics & Vision (ICIEV) · doi:10.1109/iciev.2017.8338606 · Cited by 19

Big Data Perspective for Driver/Driving Behavior

Terzi, R., Sağıroğlu, Ş., & Demi̇rezen, M. U. (2018) · IEEE Intelligent Transportation Systems Magazine · doi:10.1109/mits.2018.2879220 · Cited by 19

Management mode construction for operation and supervision of rural sewage treatment facilities: Towards the information-to-intelligence strategy

Song, X., Liu, R., Yu, Q., Sheng, X., & Chen, L. (2020) · Bioresource Technology Reports · doi:10.1016/j.biteb.2020.100481 · Cited by 19

Anti Money Laundering detection using Naïve Bayes Classifier

Kumar, A., Das, S., & Tyagi, V. (2020) · IEEE International Conference on Computing, Power and Communication Technologies (IC2PCT) · doi:10.1109/gucon48875.2020.9231226 · Cited by 19

Data science in organizations: Conceptualizing its breakthroughs and blind spots

Cybulski, J. L., & Scheepers, R. (2021) · Journal of Information Technology · doi:10.1177/0268396220988539 · Cited by 22

Linking knowledge management capabilities and the mediating role of the big data capabilities for enterprise value-adding processes

Shaqrah, A. A., & Alzighaibi, A. R. (2021) · VINE Journal of Information and Knowledge Management Systems · doi:10.1108/vjikms-05-2020-0087 · Cited by 20

A smart reporting framework as an application of multi-agent system in machining industry

Yahouni, Z., Ladj, A., Belkadi, F., Meski, O., & Ritou, M. (2021) · International Journal of Computer Integrated Manufacturing · doi:10.1080/0951192x.2021.1901312 · Cited by 19

Personalization in airline revenue management: an overview and future outlook

Buyruk, M., & Güner, E. (2021) · Journal of Revenue and Pricing Management · doi:10.1057/s41272-021-00342-x · Cited by 20

aiSTROM–A Roadmap for Developing a Successful AI Strategy

Herremans, D. (2021) · IEEE Access · doi:10.1109/access.2021.3127548 · Cited by 26

A Comparative Perspective on Technologies of Big Data Value Chain

Aydın, A. A. (2023) · IEEE Access · doi:10.1109/access.2023.3323160 · Cited by 19

A framework to specify big data driven complex cyber physical control systems

Zhang, L. (2014) · IEEE International Conference on Information and Automation (ICIA) · doi:10.1109/icinfa.2014.6932715 · Cited by 19

A Science Gateway Cloud With Cost-Adaptive VM Management for Computational Science and Applications

Kim, S.-H., Kang, D.-K., Kim, W., Chen, M., & Youn, C. (2016) · IEEE Systems Journal · doi:10.1109/jsyst.2015.2501750 · Cited by 19

A Grey Theory Based Approach to Big Data Risk Management Using FMEA

Silva, M. M., Poleto, T., Silva, L. C. E., de Gusmão, A. P. H., & Costa, A. P. C. S. (2016) · Mathematical Problems in Engineering · doi:10.1155/2016/9175418 · Cited by 19

An Application of the IoT in Belt Conveyor Systems

Lodewijks, G., Li, W., Pang, Y., & Jiang, X. (2016) · Lecture notes in computer science · doi:10.1007/978-3-319-45940-0_31 · Cited by 19

Using Fuzzy Concept Lattice for Intelligent Disease Diagnosis

Zou, C., & Deng, H. (2016) · IEEE Access · doi:10.1109/access.2016.2638848 · Cited by 19

Testing of transactional services in NoSQL key-value databases

González-Aparicio, M. T., Younas, M., Tuya, J., & Casado, R. (2017) · Future Generation Computer Systems · doi:10.1016/j.future.2017.07.004 · Cited by 19

Modeling Attack Process of Advanced Persistent Threat Using Network Evolution

Niu, W., Zhang, X., Yang, G., Chen, R., & Wang, D. (2017) · IEICE Transactions on Information and Systems · doi:10.1587/transinf.2016inp0007 · Cited by 19

Relevance of Big Data for Business and Management. Exploratory Insights (Part I)

Ogrean, C. (2018) · Studies in Business and Economics · doi:10.2478/sbe-2018-0027 · Cited by 19

The Role of IoT and Big Data in Modern Technological Arena: A Comprehensive Study

Priyadarshini, S. B. B., BhusanBagjadab, A., & Mishra, B. K. (2018) · Intelligent systems reference library · doi:10.1007/978-3-030-04203-5_2 · Cited by 19

Smart Grids and Industry 4.0

Tuttokmağı, Ö., & Kaygusuz, A. (2018) · International Artificial Intelligence and Data Processing Symposium (IDAP) · doi:10.1109/idap.2018.8620887 · Cited by 19

Context Aware Computing Systems: A survey

Gandodhar, P., & Chaware, S. M. (2018) · International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC) · doi:10.1109/i-smac.2018.8653786 · Cited by 19

Big Data Technologies using SVM (Case Study: Surface Water Classification on Regional Water Utility Company in Surabaya)

Budiarti, R. P. N., Sukaridhoto, S., Hariadi, M., & Purnomo, M. H. (2019) · International Conference on Computer Science, Information Technology, and Electrical Engineering (ICOMITEE) · doi:10.1109/icomitee.2019.8920823 · Cited by 19

Traffic and Transportation Smart with Cloud Computing on Big Data.

Wang, X., & Li, Z. (2016) · Cited by 19

MPTCP Meets Big Data: Customizing Transmission Strategy for Various Data Flows

Xing, Y., Han, J., Xue, K., Liu, J., Pan, M., & Hong, P. (2020) · IEEE Network · doi:10.1109/mnet.011.1900438 · Cited by 19

Big data analysis

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