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

(2013) · Choice Reviews Online · doi:10.5860/choice.50-6804 · Cited by 3,657

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

Museums creating value and developing intellectual capital by technology

Romanelli, M. (2018) · Meditari Accountancy Research · doi:10.1108/medar-10-2017-0225 · Cited by 28

Can data center green reform facilitate urban green technology innovation? Evidence from China

Liu, Y., & Yang, Z. (2023) · Environmental Science and Pollution Research · doi:10.1007/s11356-023-26439-x · Cited by 27

Access Control with Delegated Authorization Policy Evaluation for Data-Driven Microservice Workflows

Preuveneers, D., & Joosen, W. (2017) · Future Internet · doi:10.3390/fi9040058 · Cited by 27

Three Hierarchical Levels of Big-Data Market Model Over Multiple Data Sources for Internet of Things

Jang, B., Park, S., Lee, J., & Hahn, S.-G. (2018) · IEEE Access · doi:10.1109/access.2018.2845105 · Cited by 27

A multimodal fusion based framework to reinforce IDS for securing Big Data environment using Spark

Donkal, G., & Verma, G. K. (2018) · Journal of Information Security and Applications · doi:10.1016/j.jisa.2018.10.001 · Cited by 27

Big Data Analytics: The New Boundaries of Retail Location Decision Making

Aversa, J. M., Doherty, S. T., & Hernández, T. (2018) · Papers in Applied Geography · doi:10.1080/23754931.2018.1527720 · Cited by 27

MapReduce: an infrastructure review and research insights

Maleki, N., Rahmani, A. M., & Conti, M. (2019) · The Journal of Supercomputing · doi:10.1007/s11227-019-02907-5 · Cited by 27

Is It Possible to Predict Cardiac Death?

Ricciardi, C., Cantoni, V., Green, R., Improta, G., & Cesarelli, M. (2019) · World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany · doi:10.1007/978-3-030-31635-8_101 · Cited by 27

Inter-Planetary File System Enabled Blockchain Solution For Securing Healthcare Records

Marangappanavar, R. K., & Kiran, M. (2020) · ISEA Conference on Security and Privacy (ISEA-ISAP) · doi:10.1109/isea-isap49340.2020.235016 · Cited by 27

Chronic Disease Prediction Using Deep Learning

Mishra, J., & Tarar, S. (2020) · Communications in computer and information science · doi:10.1007/978-981-15-6634-9_19 · Cited by 27

Semantic-based Big Data integration framework using scalable distributed ontology matching strategy

Mountasser, I., Ouhbi, B., Hdioud, F., & Frikh, B. (2021) · Distributed and Parallel Databases · doi:10.1007/s10619-021-07321-6 · Cited by 27

Enhancing data quality to mine credible patterns

Imran, M., & Ahmad, A. (2021) · Journal of Information Science · doi:10.1177/01655515211013693 · Cited by 28

HybridML: Open source platform for hybrid modeling

Merkelbach, K., Schweidtmann, A. M., Müller, Y., Schwoebel, P., Mhamdi, A., Mitsos, A., Schuppert, A., Mrziglod, T., & Schneckener, S. (2022) · Computers & Chemical Engineering · doi:10.1016/j.compchemeng.2022.107736 · Cited by 32

Exploring the integration of blockchain technology, physical unclonable function, and machine learning for authentication in cyber-physical systems

Al-Ghuraybi, H. A., AlZain, M. A., & Soh, B. (2023) · Multimedia Tools and Applications · doi:10.1007/s11042-023-16979-2 · Cited by 31

A hybrid integrated architecture for energy consumption prediction

Maté, A., Peral, J., Ferrández, A., Gil, D., & Trujillo, J. C. (2016) · Future Generation Computer Systems · doi:10.1016/j.future.2016.03.020 · Cited by 27

Big Data representation for grade analysis through Hadoop framework

Verma, C., & Pandey, R. (2016) · International Conference on Cloud Computing, Data Science & Engineering (Confluence) · doi:10.1109/confluence.2016.7508134 · Cited by 27

Is big data for everyone? the challenges of big data adoption in SMEs

Shah, S. R., Soriano, C. B., & Coutroubis, A. D. (2017) · IEEE International Conference on Industrial Engineering and Engineering Management (IEEM) · doi:10.1109/ieem.2017.8290002 · Cited by 28

Public libraries: roles in Big Data

Zhan, M., & Widén, G. (2017) · The Electronic Library · doi:10.1108/el-06-2016-0134 · Cited by 27

NVQuery: Efficient Query Processing in Nonvolatile Memory

Imani, M., Gupta, S., Sharma, S., & Simunic, T. (2018) · IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems · doi:10.1109/tcad.2018.2819080 · Cited by 27

Integrating the Principles of Green Marketing by Using Big Data. Good Practices

Andronie, M., Gârdan, D. A., Dumitru, I., Gârdan, I. P., Andronie, I. E., & Uţă, C. (2019) · Amfiteatru Economic · doi:10.24818/ea/2019/50/258 · Cited by 27

Big data applications in intelligent transport systems: a bibliometric analysis and review

Hassan, M., Mahin, H. D., Nafees, A. A., Paul, A., & Shraban, S. S. (2025) · Discover Civil Engineering · doi:10.1007/s44290-025-00205-z · Cited by 26

Big-Data Processing Techniques and Their Challenges in Transport Domain

Chandio, A. A., Ahmed, Chandio, Nikos, Tziritas, Chengzhong, & Xu (2015) · ZTE communications · doi:10.3969/j.issn.1673-5188.2015.01.007 · Cited by 26

Parallel set similarity join on big data based on Locality-Sensitive Hashing

Sohrabi, M. K., & Azgomi, H. (2017) · Science of Computer Programming · doi:10.1016/j.scico.2017.04.006 · Cited by 26

Patterns for Distributed Real-Time Stream Processing

Val, P. B., Fernández, N., Fernández, L. S., & Fisteus, J. A. (2017) · IEEE Transactions on Parallel and Distributed Systems · doi:10.1109/tpds.2017.2716929 · Cited by 26

Large Scale Medical Data Mining for Accurate Diagnosis: A Blueprint

Kamal, M. S., Dey, N., & Ashour, A. S. (2017) · Scalable computing and communications · doi:10.1007/978-3-319-58280-1_7 · Cited by 27

The Method of Big Data Processing for Distance Educational System

Shakhovska, N., Вовк, О., Hasko, R., & Kryvenchuk, Y. P. (2017) · Advances in intelligent systems and computing · doi:10.1007/978-3-319-70581-1_33 · Cited by 26

A Secure Multi-Tier Mobile Edge Computing Model for Data Processing Offloading Based on Degree of Trust

Gimeno, F. J. M., Mora, H., Marcos-Jorquera, D., & Volckaert, B. (2018) · Sensors · doi:10.3390/s18103211 · Cited by 26

Real-Time Heart Arrhythmia Detection Using Apache Spark Structured Streaming

Ilbeigipour, S., Albadvi, A., & Noughabi, E. A. (2021) · Journal of Healthcare Engineering · doi:10.1155/2021/6624829 · Cited by 26

Driving or driven by others? A dynamic perspective on how data-driven start-ups strategize across different network roles in digitalized business networks

Mosch, P., Winkler, C., Eggert, C.-G., Schumann, J. H., Obermaier, R., & Ulaga, W. (2022) · Industrial Marketing Management · doi:10.1016/j.indmarman.2022.01.023 · Cited by 26

GeoAI Technologies and Their Application Areas in Urban Planning and Development: Concepts, Opportunities and Challenges in Smart City (Kuwait, Study Case)

Alastal, A. I., & Shaqfa, A. H. (2022) · Journal of Data Analysis and Information Processing · doi:10.4236/jdaip.2022.102007 · Cited by 33

A review on offloading in fog-based Internet of Things: Architecture, machine learning approaches, and open issues

Lone, K., & Sofi, S. A. (2023) · High-Confidence Computing · doi:10.1016/j.hcc.2023.100124 · Cited by 26

Integrating IoT Analytics into Marketing Decision Making: A Smart Data-Driven Approach

Rajan, P. (2024) · International Journal of Data Informatics and Intelligent Computing · doi:10.59461/ijdiic.v3i1.92 · Cited by 26

Performance overview of an artificial intelligence in biomedics: a systematic approach

Patil, S., Patil, C. R., Patil, S. S., & Patil, S. S. (2018) · International Journal of Information Technology · doi:10.1007/s41870-018-0243-8 · Cited by 26

Towards An Efficient Real-time Approach To Loan Credit Approval Using Deep Learning

Abakarim, Y., Lahby, M., & Attioui, A. (2018) · International Symposium on Signal, Image, Video and Communications (ISIVC) · doi:10.1109/isivc.2018.8709173 · Cited by 26

Synaptic metaplasticity of protonic/electronic coupled oxide neuromorphic transistor

Ren, Z. Y., Zhu, L. Q., Yu, F., Xiao, H. J., Xiong, W., & Ge, Z. Y. (2019) · Organic Electronics · doi:10.1016/j.orgel.2019.07.028 · Cited by 26

Analytics for the Internet of Things: A SurveyPreprint

Siow, E., Tiropanis, T., & Hall, W. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1807.00971 · Cited by 26

Predicting science achievement scores with machine learning algorithms: a case study of OECD PISA 2015–2018 data

Açışlı, S., & Yeşilkanat, C. M. (2023) · Neural Computing and Applications · doi:10.1007/s00521-023-08901-6 · Cited by 29

BIG DATA-DRIVEN DECISION MAKING IN PROJECT MANAGEMENT: A COMPARATIVE ANALYSIS

Rahaman, M. A., Rozony, F. Z., Mazumder, M. S. A., & Haque, M. N. (2024) · Academic journal on science, technology, engineering & mathematics education. · doi:10.69593/ajsteme.v4i03.88 · Cited by 28

The Role of Mutual Information Estimator Choice in Feature Selection: An Empirical Study on mRMR

Papaioannou, N., Myllis, G., Tsimpiris, A., & Vrana, V. G. (2025) · Information · doi:10.3390/info16090724 · Cited by 25

Efficient query processing in crossbar memory

Imani, M., Gupta, S., Arredondo, A., & Rosing, T. (2017) · International Symposium on Low Power Electronics and Design (ISLPED) · doi:10.1109/islped.2017.8009204 · Cited by 25

Big Data Model Simulation on a Graph Database for Surveillance in Wireless Multimedia Sensor Networks

Küçükkeçeci, C., & Yazıcı, A. (2017) · Big Data Research · doi:10.1016/j.bdr.2017.09.003 · Cited by 25

Efficient Big Data Modelling and Organization for Hadoop Hive-Based Data Warehouses

Costa, E., Costa, C., & Santos, M. Y. (2017) · Lecture notes in business information processing · doi:10.1007/978-3-319-65930-5_1 · Cited by 25

A comparative analysis of differential privacy vs other privacy mechanisms for Big Data

Begum, S. H., & Nausheen, F. (2018) · International Conference on Inventive Systems and Control (ICISC) · doi:10.1109/icisc.2018.8399125 · Cited by 25

Advance on large scale near-duplicate video retrieval

Shen, L., Hong, R., & Hao, Y. (2020) · Frontiers of Computer Science · doi:10.1007/s11704-019-8229-7 · Cited by 24

A fast parallel attribute reduction algorithm using Apache Spark

Yin, L., Qin, L., Jiang, Z., & Xu, X. (2020) · Knowledge-Based Systems · doi:10.1016/j.knosys.2020.106582 · Cited by 25

Tecnologías de la información y las Comunicaciones en la era de la cuarta revolución industrial: Tendencias Tecnológicas y desafíos en la educación en Ingeniería

Sánchez, L. Y. B. (2020) · Entre ciencia e ingeniería · doi:10.31908/19098367.2057 · Cited by 31

Delineating the Implications of Dispersing Teams and Teleworking in an Agile UK Construction Sector

Burton, E., Edwards, D. J., Roberts, C. J., Chileshe, N., & Lai, J. H. K. (2021) · Sustainability · doi:10.3390/su13179981 · Cited by 28

Review on status of groundwater database and application prospect in deep-time digital earth plan

Qiu, W., Ma, T., Wang, Y., Cheng, J., Su, C., & Li, J. (2022) · Geoscience Frontiers · doi:10.1016/j.gsf.2022.101383 · Cited by 25

Identifying the most suitable machine learning approach for a road digital twin

Chen, K., Torbaghan, M. E., Chu, M., Zhang, L., & García, Á. (2021) · Proceedings of the Institution of Civil Engineers - Smart Infrastructure and Construction · doi:10.1680/jsmic.22.00003 · Cited by 28

The Anatomy of Big Data: Concepts, Principles and Challenges

Singh, J., Singh, G., & Verma, A. (2022) · International Conference on Advanced Computing and Communication Systems (ICACCS) · doi:10.1109/icaccs54159.2022.9785082 · Cited by 25

Forestry Big Data: A Review and Bibliometric Analysis

Gao, W., Qiu, Q., Yuan, C., Shen, X., Cao, F., Wang, G., & Wang, G. (2022) · Forests · doi:10.3390/f13101549 · Cited by 34

Barriers to big data analytics (BDA) implementation in manufacturing supply chains

Dehkhodaei, A., Amiri, B., Farsijani, H., & Raad, A. (2023) · Journal of Management Analytics · doi:10.1080/23270012.2023.2179430 · Cited by 25

Fuzzy c -Means and Cluster Ensemble with Random Projection for Big Data Clustering

Ye, M., Liu, W., Wei, J., & Hu, X. (2016) · Mathematical Problems in Engineering · doi:10.1155/2016/6529794 · Cited by 25

Handling Big Data in the Era of Internet of Things (IoT)

Papadokostaki, K., Mastorakis, G. N., Panagiotakis, S., Mavromoustakis, C. X., Dobre, C., & Batalla, J. M. (2016) · Studies in big data · doi:10.1007/978-3-319-45145-9_1 · Cited by 25

Higher Education Disruption Through IoT and Big Data: A Conceptual Approach

Moreira, F., Ferreira, M. J., & Cardoso, A. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-58509-3_31 · Cited by 25

A Fine‐Grained Distribution Approach for ETL Processes in Big Data Environments

Bala, M., Boussaïd, O., & Alimazighi, Z. (2017) · Data & Knowledge Engineering · doi:10.1016/j.datak.2017.08.003 · Cited by 25

Filter Variable Selection Algorithm Using Risk Ratios for Dimensionality Reduction of Healthcare Data for Classification

Bodur, E. K., & Atsa’am, D. D. (2019) · Processes · doi:10.3390/pr7040222 · Cited by 25

Big Data and HPC Convergence for Smart Infrastructures: A Review and Proposed Architecture

Usman, S., Mehmood, R., & Katib, I. A. (2019) · EAI/Springer Innovations in Communication and Computing · doi:10.1007/978-3-030-13705-2_23 · Cited by 25

Comparative Study of Big Data Frameworks

Gupta, H. K., & Parveen, R. (2019) · International Conference on Issues and Challenges in Intelligent Computing Techniques · doi:10.1109/icict46931.2019.8977680 · Cited by 25

Anomaly Detection and Redundancy Elimination of Big Sensor Data in Internet of ThingsPreprint

Xie, S., & Chen, Z. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1703.03225 · Cited by 25

Multiple Disease Risk Assessment With Uniform Model Based on Medical Clinical Notes

Shi, X., Hu, Y., Zhang⋆, Y., Li, W., Hao, Y., Alelaiwi, A. A., Rahman, S. M. M., & Hossain, M. S. (2016) · IEEE Access · doi:10.1109/access.2016.2614541 · Cited by 25

A resource-frugal probabilistic dictionary and applications in bioinformatics

Marchet, C., Lecompte, L., Limasset, A., Bittner, L., & Peterlongo, P. (2018) · Discrete Applied Mathematics · doi:10.1016/j.dam.2018.03.035 · Cited by 27

The method of big data processing

Shakhovska, N. (2017) · IEEE International Conference on Computer Sciences and Information Technologies (CSIT) · doi:10.1109/stc-csit.2017.8098751 · Cited by 24

Incremental adaptive semi-supervised fuzzy clustering for data stream classification

Casalino, G., Castellano, G., & Mencar, C. (2018) · IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS) · doi:10.1109/eais.2018.8397172 · Cited by 24

A3-Storm: topology-, traffic-, and resource-aware storm scheduler for heterogeneous clusters

Muhammad, A., & Aleem, M. (2020) · The Journal of Supercomputing · doi:10.1007/s11227-020-03289-9 · Cited by 24

Machine learning models for the prediction of acuity and variability of eye-positioning using features extracted from oculography

Improta, G., Ricciardi, C., Cesarelli, G., D’Addio, G., Bifulco, P., & Cesarelli, M. (2020) · Health and Technology · doi:10.1007/s12553-020-00449-y · Cited by 24

Mapping the Big Data Landscape: Technologies, Platforms and Paradigms for Real-Time Analytics of Data Streams

Dubuc, T. T., Stahl, F. T., & Roesch, E. B. (2020) · IEEE Access · doi:10.1109/access.2020.3046132 · Cited by 29

Planning Digital Transformation of Care in Rural Areas

Drobež, E., Rogelj, V., Bogataj, D., & Bogataj, M. (2021) · IFAC-PapersOnLine · doi:10.1016/j.ifacol.2021.10.542 · Cited by 30

A Survey on Predictive Maintenance Through Big Data

Patwardhan, A., Verma, A. K., & Kumar, U. (2015) · Lecture notes in mechanical engineering · doi:10.1007/978-3-319-23597-4_31 · Cited by 24

Big Data and Business Analytics in the Supply Chain: A Review of the Literature

Isasi, N. K. G., Frazzon, E. M., & Maldonado, M. U. (2015) · IEEE Latin America Transactions · doi:10.1109/tla.2015.7387245 · Cited by 24

H2Hadoop: Improving Hadoop Performance Using the Metadata of Related Jobs

Alshammari, H. H., Lee, J., & Bajwa, H. (2016) · IEEE Transactions on Cloud Computing · doi:10.1109/tcc.2016.2535261 · Cited by 24

Proactive Maintenance as Success Factor for Use-Oriented Product-Service Systems

Exner, K., Schnürmacher, C., Adolphy, S., & Stark, R. (2017) · Procedia CIRP · doi:10.1016/j.procir.2017.03.024 · Cited by 27

A big data architecture for managing oceans of data and maritime applications

Lytra, I., Vidal, M.-E., Orlandi, F., & Attard, J. (2017) · IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC) · doi:10.1109/ice.2017.8280019 · Cited by 24

Databased prediction of order-specific transition times

Schuh, G., Prote, J.-P., Sauermann, F., & Franzkoch, B. (2019) · CIRP Annals · doi:10.1016/j.cirp.2019.03.008 · Cited by 24

Employability traits for engineers: A competencies-based approach

Pais‐Montes, C., Seoane, M. J. F., & López-Bermúdez, B. (2019) · Industry and Higher Education · doi:10.1177/0950422219854616 · Cited by 24

A Sticky Policy Framework for Big Data Security

Li, S., ZHANG, T., Gao, J. Z., & Park, Y. (2015) · IEEE International Conference on Big Data Computing Service and Applications (BigDataService) · doi:10.1109/bigdataservice.2015.71 · Cited by 23

Mining Big Data in biomedicine and health care

Fodeh, S. J., & Zeng, Q. T. (2016) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2016.09.014 · Cited by 23

Routing in Black Box: Modularized Load Balancing for Multipath Data Center Networks

Fan, F., Hu, B., & Yeung, K. L. (2019) · IEEE Conference on Computer Communications (INFOCOM) · doi:10.1109/infocom.2019.8737650 · Cited by 23

Data literacy for safety professionals in safety management: A theoretical perspective on basic questions and answers

Wang, B., Wu, C., & Huang, L. (2019) · Safety Science · doi:10.1016/j.ssci.2019.04.002 · Cited by 23

Artificial Intelligence Applications for Event Management and Marketing

Ergen, F. D. (2020) · Advances in marketing, customer relationship management, and e-services book series · doi:10.4018/978-1-7998-4954-4.ch012 · Cited by 23

Machine learning in spectral domain

Giambagli, L., Buffoni, L., Carletti, T., Nocentini, W., & Fanelli, D. (2021) · RePEc: Research Papers in Economics · Cited by 23

Rotation Forest for Big Data

Juez-Gil, M., González, Á. A., Rodríguez, J. J., Nozal, C. L., & García‐Osorio, C. (2021) · Information Fusion · doi:10.1016/j.inffus.2021.03.007 · Cited by 23

Filtering active moments in basketball games using data from players tracking systems

Facchinetti, T., Metulini, R., & Zuccolotto, P. (2021) · Annals of Operations Research · doi:10.1007/s10479-021-04391-8 · Cited by 23

Parallel incremental efficient attribute reduction algorithm based on attribute tree

Ding, W., Qin, T., Shen, X., Ju, H., Wang, H., Huang, J., & Li, M. (2022) · Information Sciences · doi:10.1016/j.ins.2022.08.044 · Cited by 23

The impact of big data analytics on organizational sustainability: The influencing factors of autonomous research and development and absorptive capacity

Arshad, M., Yu, C. K., Qadir, A., Ahmad, W., & Rafique, M. (2022) · International Journal of Engineering Business Management · doi:10.1177/18479790221141537 · Cited by 24

Big data application and corporate investment decisions: Evidence from A-share listed companies in China

Wang, L., Wu, Y., Huang, Z., & Wang, Y. (2024) · International Review of Financial Analysis · doi:10.1016/j.irfa.2024.103331 · Cited by 26

AHP Model for the Big Data Analytics Platform Selection

Lněnička, M. (2015) · Acta Informatica Pragensia · doi:10.18267/j.aip.64 · Cited by 23

Scalable Architecture for Personalized Healthcare Service Recommendation Using Big Data Lake

Rangarajan, S., Liu, H., Wang, H., & Wang, C.-L. (2018) · Lecture notes in business information processing · doi:10.1007/978-3-319-76587-7_5 · Cited by 23

The Application of Downhole Vibration Factor in Drilling Tool Reliability Big Data Analytics—A Review

Ren, Y., Wang, N., Jiang, J., Zhu, J., Song, G., & Chen, X. (2018) · ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part B Mechanical Engineering · doi:10.1115/1.4040407 · Cited by 23

Measuring the interdisciplinarity of Big Data research: a longitudinal study

Hu, J., & Zhang, Y. (2018) · Online Information Review · doi:10.1108/oir-12-2016-0361 · Cited by 23

A Survey on Big Data Pre-processing

Guan, Z., Ji, T., Xu, Q., Ma, Y., & Hong, X. (2017) · International Conference on Applied Computing and Information Technology / International Conference on Computational Science and Intelligence (ACIT-CSI) · doi:10.1109/acit-csii-bcd.2017.49 · Cited by 23

Measuring risk of missing transfers in public transit systems using high-resolution schedule and real-time bus location data

Liu, L., & Miller, H. J. (2020) · Urban Studies · doi:10.1177/0042098020919323 · Cited by 23

Cutpoint Temperature Surrogate Modeling for Distillation Yields and Properties

Franzoi, R. E., Menezes, B. C., Kelly, J. D., Gut, J. A. W., & Grossmann, I. E. (2020) · Industrial & Engineering Chemistry Research · doi:10.1021/acs.iecr.0c02868 · Cited by 23

Digital Forensics vs. Anti-Digital Forensics: Techniques, Limitations and RecommendationsPreprint

Yaacoub, J.-P. A., Noura, H., Salman, O., & Chehab, A. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2103.17028 · Cited by 23

Performance Analysis and Optimization on Scheduling Stochastic Cloud Service Requests: A Survey

Wang, S., Li, X., Sheng, Q. Z., & Beheshti, A. (2022) · IEEE Transactions on Network and Service Management · doi:10.1109/tnsm.2022.3181145 · Cited by 22

Real-time monitoring and optimization methods for user-side energy management based on edge computing

Huang, J., Zhou, S., Li, G., & Shen, Q. (2025) · Scientific Reports · doi:10.1038/s41598-025-07592-4 · Cited by 30

A review of transport carbon emissions: insights from artificial intelligence and big data

Ouyang, S., Zhao, P., & Gong, Z. (2025) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2025.146906 · Cited by 24

Self-Healing REST Services Using Artificial Intelligence in Multi-Cloud Environments

Jaiswal, I. A. (2024) · Scientific Journal of Artificial Intelligence and Blockchain Technologies · doi:10.63345/sjaibt.v1.i3.201 · Cited by 22

Big Data: A Survey - The New Paradigms, Methodologies and Tools

Caldarola, E. G., & Rinaldi, A. M. (2015) · International Conference on Data Science, Technology and Applications (DATA) · doi:10.5220/0005580103620370 · Cited by 22

Evaluating SQL-on-Hadoop for Big Data Warehousing on Not-So-Good Hardware

Santos, M. Y., Costa, C., Galvão, J., Andrade, C. S., Martinho, B., Lima, F. V., & Costa, E. (2017) · International Database Engineering and Applications Symposium (IDEAS) · doi:10.1145/3105831.3105842 · Cited by 22

Big data analysis

Rasheed, R. T., Mohammed, M. A., & Ţăpuş, N. (2021) · Mesopotamian Journal of Big Data · doi:10.58496/mjbd/2021/004 · Cited by 3

Big data: related technologies, challenges and future prospects

Chen, M., Mao, S., Zhang, Y., & Leung, V. C. (2014) · CERN Document Server (European Organization for Nuclear Research) · Cited by 31

Big Data Generation and Acquisition

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