Data mining with big data

Twitter mood predicts the stock market

Bollen, J., Mao, H., & Zeng, X. (2011) · Journal of Computational Science · doi:10.1016/j.jocs.2010.12.007 · Cited by 5,206

Network Analysis in the Social Sciences

Borgatti, S. P., Mehra, A., Brass, D. J., & Labianca, G. (2009) · Science · doi:10.1126/science.1165821 · Cited by 4,280

The spread of behavior in an online social network experiment

Centola, D. (2010) · Science · doi:10.1126/science.1185231 · Cited by 2,692

Mining of Massive Datasets

Rajaraman, A., & Ullman, J. D. (2011) · Cambridge University Press eBooks · doi:10.1017/cbo9781139058452 · Cited by 2,307

How to generate and exchange secrets

Yao, A. (1986) · 27th Annual Symposium on Foundations of Computer Science (sfcs 1986) · doi:10.1109/sfcs.1986.25 · Cited by 2,281

Mining high-speed data streams

Domingos, P., & Hulten, G. (2000) · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/347090.347107 · Cited by 2,217

Privacy-Preserving Public Auditing for Secure Cloud Storage

Wang, C., Chow, S. S. M., Wang, Q., Ren, K., & Lou, W. (2011) · IEEE Transactions on Computers · doi:10.1109/tc.2011.245 · Cited by 1,382

Map-Reduce for Machine Learning on Multicore

Chu, C.-T., Kim, S. K., Lin, Y.-A., Yu, Y., Bradski, G. R., Ng, A. Y., & Olukotun, K. (2007) · The MIT Press eBooks · doi:10.7551/mitpress/7503.003.0040 · Cited by 1,247

The Square Kilometre Array

Dewdney, P. E., Hall, P. J., Schilizzi, R. T., & Lazio, T. J. W. (2009) · Proceedings of the IEEE · doi:10.1109/jproc.2009.2021005 · Cited by 1,196

Challenges and opportunities with big data

Labrinidis, A., & Jagadish, H. V. (2012) · Proceedings of the VLDB Endowment · doi:10.14778/2367502.2367572 · Cited by 1,070

MISFP-Growth: Hadoop-Based Frequent Pattern Mining with Multiple Item Support

Wang, C.-S., & Chang, J.-Y. (2019) · Applied Sciences · doi:10.3390/app9102075 · Cited by 15

Local Graph Edge Partitioning with a Two-Stage Heuristic Method

Ji, S., Bu, C., Li, L., & Wu, X. (2019) · IEEE International Conference on Distributed Computing Systems (ICDCS) · doi:10.1109/icdcs.2019.00031 · Cited by 15

A Collaborative Data Publishing Model with Privacy Preservation Using Group‐Based Classification and Anonymity

J, C. M. B. M., Antonykumar, K., Ravikumar, S., & Kulkarni, Y. R. (2022) · doi:10.1002/9781119763499.ch3 · Cited by 15

Demographic and Indication-Specific Characteristics Have Limited Association With Social Network Engagement: Evidence From 24,954 Members of Four Health Care Support Groups

van Mierlo, T., Li, X., Hyatt, D., & Ching, A. T. (2017) · Journal of Medical Internet Research · doi:10.2196/jmir.6330 · Cited by 14

Smart Data-Enabled Conservation and Knowledge Generation for Architectural Heritage System

Rao, Z., & Wang, G. (2025) · Buildings · doi:10.3390/buildings15122122 · Cited by 14

Comparative Analysis of Information Extraction Techniques for Data Mining

Verma, A., Kaur, I., & Arora, N. (2016) · Indian Journal of Science and Technology · doi:10.17485/ijst/2016/v9i11/80464 · Cited by 14

An evolving Takagi-Sugeno model based on aggregated trapezium clouds for anomaly detection in large datasets

Wang, M.-X., & Wang, J. (2017) · Journal of Intelligent & Fuzzy Systems · doi:10.3233/jifs-16254 · Cited by 14

TT-TSVD: A Multi-modal Tensor Train Decomposition with Its Application in Convolutional Neural Networks for Smart Healthcare

Liu, D., Yang, L. T., Wang, P., Zhao, R., & Zhang, Q. (2022) · ACM Transactions on Multimedia Computing Communications and Applications · doi:10.1145/3491223 · Cited by 14

A multi-granularity information fusion method based on logistic regression model and Dempster-Shafer evidence theory and its application

Zhao, H., Mi, J., & Liang, M. (2022) · International Journal of Machine Learning and Cybernetics · doi:10.1007/s13042-022-01584-w · Cited by 14

Road Infrastructure Safety Management: Proactive Safety Tools to Evaluate Potential Conditions of Risk

Serrone, G. D., Cantisani, G., Peluso, P., Coppa, I., Mancinetti, M., & Bianchini, B. (2023) · Transportation research procedia · doi:10.1016/j.trpro.2023.02.227 · Cited by 14

Optimal nonlinear dynamic sparse model selection and Bayesian parameter estimation for nonlinear systems

Adeyemo, S., & Bhattacharyya, D. (2023) · Computers & Chemical Engineering · doi:10.1016/j.compchemeng.2023.108502 · Cited by 14

Optimal feature with modified bi-directional long short-term memory for big data classification in healthcare application

Kamble, S., Arunalatha, J. S., & Venugopal, K. R. (2024) · International Journal of Information Technology · doi:10.1007/s41870-024-02065-9 · Cited by 14

Exploring Qualitative Data: the use of Big Data technology as support in strategic decision-making

Bertei, M., Marchi, L., & Buoncristiani, D. (2015) · The International Journal of Digital Accounting Research · doi:10.4192/1577-8517-v15_4 · Cited by 14

Universal Nonlinear Regression on High Dimensional Data Using Adaptive Hierarchical Trees

Khan, F., Kari, D., Karatepe, I. A., & Kozat, S. S. (2016) · IEEE Transactions on Big Data · doi:10.1109/tbdata.2016.2555323 · Cited by 14

Toward Personalized Vibrotactile Support When Learning Motor Skills

Santos, O. C. (2017) · Algorithms · doi:10.3390/a10010015 · Cited by 14

Sensitivity-Based Anonymization of Big Data

Al-Zobbi, M., Shahrestani, S. A., & Ruan, C. (2016) · IEEE Conference on Local Computer Networks Workshops (LCN Workshops) · doi:10.1109/lcn.2016.029 · Cited by 14

Enriched Over_Sampling Techniques for Improving Classification of Imbalanced Big Data

Patil, S. S., & Sonavane, S. P. (2017) · IEEE International Conference on Big Data Computing Service and Applications (BigDataService) · doi:10.1109/bigdataservice.2017.19 · Cited by 14

A benchmarking study of classification techniques for behavioral data

Cnudde, S. D., Martens, D., Evgeniou, T., & Provost, F. J. (2019) · International Journal of Data Science and Analytics · doi:10.1007/s41060-019-00185-1 · Cited by 13

Big Data Analysis in Cloud and Machine Learning

Sharma, N., & Shamkuwar, M. (2018) · Studies in big data · doi:10.1007/978-981-13-0550-4_3 · Cited by 14

Genetic Programming Based on Error Decomposition: A Big Data Approach

Tahmassebi, A., & Gandomi, A. H. (2018) · Genetic and evolutionary computation · doi:10.1007/978-3-319-90512-9_9 · Cited by 14

Hierarchical feature extraction based on discriminant analysis

Liu, X., & Zhao, H. (2019) · Applied Intelligence · doi:10.1007/s10489-019-01418-3 · Cited by 14

Semi-autonomous methodology to validate and update customer needs database through text data analytics

Bigorra, A. M., Isaksson, O., & Karlberg, M. (2020) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2020.102073 · Cited by 14

Balancing computational complexity and generalization ability: A novel design for ELM

Ragusa, E., Gastaldo, P., Zunino, R., & Cambria, E. (2020) · Neurocomputing · doi:10.1016/j.neucom.2020.03.046 · Cited by 13

An Efficient Study of Fraud Detection System Using Ml Techniques

Isabella, S. J., Srinivasan, S., & Suseendran, G. (2020) · Lecture notes in networks and systems · doi:10.1007/978-981-15-3284-9_7 · Cited by 14

Multi-fuzzy-constrained graph pattern matching with big graph data

Liu, G., Li, L., & Wu, X. (2020) · Intelligent Data Analysis · doi:10.3233/ida-194653 · Cited by 14

IoT-enabled directed acyclic graph in spark cluster

Koo, J., Qureshi, N. M. F., Siddiqui, I. F., Abbas, A., & Bashir, A. K. (2020) · Journal of Cloud Computing Advances Systems and Applications · doi:10.1186/s13677-020-00195-6 · Cited by 14

Cyber-Physical System for Smart Grid

Osman, N. F. M., Elamin, A. A. A., Ali, E. S., & Saeed, R. A. (2020) · Advances in systems analysis, software engineering, and high performance computing book series · doi:10.4018/978-1-7998-5101-1.ch014 · Cited by 15

Recent Trends of Big Data in Precision Agriculture: a Review

Sourav, A. I., & Emanuel, A. W. R. (2021) · IOP Conference Series Materials Science and Engineering · doi:10.1088/1757-899x/1096/1/012081 · Cited by 14

Critical Analysis of Big Data Privacy Preservation Techniques and Challenges

Madan, S., Bhardwaj, K., & Gupta, S. (2021) · Advances in intelligent systems and computing · doi:10.1007/978-981-16-3071-2_23 · Cited by 16

Data analytics diffusion in the UK renewable energy sector: an innovation perspective

Kava, H., Spanaki, K., Παπαδόπουλος, Θ., Despoudi, S., Rodríguez-Espíndola, O., & Fakhimi, M. (2021) · Annals of Operations Research · doi:10.1007/s10479-021-04263-1 · Cited by 16

Benchmarking Apache Spark and Hadoop MapReduce on Big Data Classification

Tekdogan, T., & Cakmak, A. (2021) · International Conference on Cloud and Big Data Computing (ICCBDC) · doi:10.1145/3481646.3481649 · Cited by 14

Adaptive Three-Way C-Means Clustering Based on the Cognition of Distance Stability

Shen, Q., Zhang, Q., Zhao, F., & Wang, G. (2022) · Cognitive Computation · doi:10.1007/s12559-021-09965-z · Cited by 14

Intelligent deep fusion network for urban traffic flow anomaly identification

Djenouri, Y., Belhadi, A., Chen, H., & Lin, J. C. (2022) · Computer Communications · doi:10.1016/j.comcom.2022.03.021 · Cited by 14

A novel density deviation multi-peaks automatic clustering algorithm

Zhou, W., Wang, L., Han, X., Parmar, M. D., & Li, M. (2022) · Complex & Intelligent Systems · doi:10.1007/s40747-022-00798-3 · Cited by 14

Stream-DBSCAN: A Streaming Distributed Clustering Model for Water Quality Monitoring

Mu, C., Hou, Y., Zhao, J., Wei, S., & Wu, Y. (2023) · Applied Sciences · doi:10.3390/app13095408 · Cited by 14

Big Data Analytics, Processing Models, Taxonomy of Tools, V’s, and Challenges: State-of-Art Review and Future Implications

Dasari, S., & Kaluri, R. (2023) · Wireless Communications and Mobile Computing · doi:10.1155/2023/3976302 · Cited by 15

Designing software for operational decision support through coloured Petri nets

Maggi, F. M., & Westergaard, M. (2015) · Enterprise Information Systems · doi:10.1080/17517575.2015.1067723 · Cited by 14

Emerging Technologies for Health Data Analytics Research: A Conceptual Architecture

Lü, J., & Keech, M. (2015) · International Workshop on Database and Expert Systems Applications (DEXA) · doi:10.1109/dexa.2015.58 · Cited by 14

A Knowledge Perspective on Big Data by Joining Enterprise Modeling and Data Analyses

Fill, H.-G., & Johannsen, F. (2016) · Hawaii International Conference on System Sciences (HICSS) · doi:10.1109/hicss.2016.503 · Cited by 14

Theoretical Results of QoS-Guaranteed Resource Scaling for Cloud-Based MapReduce

Xu, X., Tang, M., & Tian, Y. (2016) · IEEE Transactions on Cloud Computing · doi:10.1109/tcc.2016.2535277 · Cited by 14

A Network-Science Support System for Food Chain Safety: A Case from Hungarian Cattle Production

Jóźwiak, Á. B., Milkovics, M., & Lakner, Z. (2016) · RePEc: Research Papers in Economics · doi:10.22004/ag.econ.240694 · Cited by 14

Performance Evaluation of Predictive Classifiers for Pregnancy Care

Moreira, M. W. L., Rodrigues, J. J. P. C., Oliveira, A. M. B., Saleem, K., & Neto, A. (2016) · Globecom · doi:10.1109/glocom.2016.7842136 · Cited by 14

Sampling strategies for extracting information from large data sets

Boicea, A., Truică, C., Rădulescu, F., & Buşe, E.-C. (2018) · Data & Knowledge Engineering · doi:10.1016/j.datak.2018.01.002 · Cited by 14

Mining co-location patterns from distributed spatial data

Maiti, S., & Subramanyam, R. B. V. (2018) · Journal of King Saud University - Computer and Information Sciences · doi:10.1016/j.jksuci.2018.08.010 · Cited by 14

Stirring The Cauldron: Redefining Computational Archival Science (CAS) For The Big Data Domain

Payne, N. (2018) · IEEE International Conference on Big Data (BigData) · doi:10.1109/bigdata.2018.8622594 · Cited by 14

CSMR: A Scalable Algorithm for Text Clustering with Cosine Similarity and MapReduce

Giannakouris-Salalidis, V., Plerou, A., & Sioutas, S. (2014) · Lecture notes in computer science · doi:10.1007/978-3-662-44722-2_23 · Cited by 14

Challenges of Big Data to Big Data Mining with their Processing Framework

Pandey, K. K., & Shukla, D. (2018) · International Conference on Communication Systems and Network Technologies · doi:10.1109/csnt.2018.8820282 · Cited by 14

Artificial Intelligence Based Electronic Healthcare Solution

Kim, S.-K., & Huh, J. (2021) · Lecture notes in electrical engineering · doi:10.1007/978-981-15-9343-7_81 · Cited by 14

The GWAS-MAP platform for aggregation of results of genome-wide association studies and the GWAS-MAP|homo database of 70 billion genetic associations of human traits

Shashkova, T., Gorev, D. D., Pakhomov, E., Shadrina, A. S., Sharapov, S., Tsepilov, Y. A., Karssen, L. C., & Aulchenko, Y. S. (2020) · Vavilov Journal of Genetics and Breeding · doi:10.18699/vj20.686 · Cited by 15

Sequential change-point detection in high-dimensional Gaussian graphical modelsPreprint

Keshavarz, H., Michailidis, G. C., & Atchadé, Y. F. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1806.07870 · Cited by 14

Unsupervised Feature Analysis with Class Margin OptimizationPreprint

Wang, S., Nie, F., Chang, X., Yao, L., Li, X., & Sheng, Q. Z. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1506.01330 · Cited by 14

A Tutorial on Distance Metric Learning: Mathematical Foundations, Algorithms, Experimental Analysis, Prospects and Challenges (with Appendices on Mathematical Background and Detailed Algorithms Explanation)Preprint

Suárez, J. L., García, S., & Herrera, F. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1812.05944 · Cited by 14

Challenges with big data mining: A review

Sebastian, L. R., Babu, S., & Kizhakkethottam, J. J. (2015) · International Conference on Soft-computing and Network Security (ICSNS) · doi:10.1109/icsns.2015.7292371 · Cited by 13

Big data resource service platform for the internet financial industry

Jiang, C., Ding, Z., Wang, J., & Yan, C. (2014) · Chinese Science Bulletin · doi:10.1007/s11434-014-0570-5 · Cited by 13

Users in the urban sensing process

Silva, T. H., Celes, C. S. F. S., Neto, J. B. B., Mota, V. F. S., Cunha, F. D., Ferreira, A. P. G., Ribeiro, A. I. J. T., de Melo, P. O. S. V., Almeida, J. M., & Loureiro, A. A. F. (2016) · Elsevier eBooks · doi:10.1016/b978-0-12-803663-1.00003-6 · Cited by 13

Subclass-based semi-random data partitioning for improving sample representativeness

Liu, H., Chen, S., & Cocea, M. (2018) · Information Sciences · doi:10.1016/j.ins.2018.11.002 · Cited by 13

Classification of healthcare data using hybridised fuzzy and convolutional neural network

Ramasamy, B., & Hameed, A. Z. (2019) · Healthcare Technology Letters · doi:10.1049/htl.2018.5046 · Cited by 13

A Comparison of Performance Metrics with Severely Imbalanced Network Security Big Data

Hasanin, T., Khoshgoftaar, T. M., & Leevy, J. L. (2019) · IEEE International Conference on Information Reuse and Integration (IRI) · doi:10.1109/iri.2019.00026 · Cited by 13

Big Data Infrastructure, Data Visualisation and Challenges

Venkatraman, R., & Venkatraman, S. (2019) · International Conference on Big Data and Internet of Things (BDIOT) · doi:10.1145/3361758.3361768 · Cited by 13

CRISP-eSNeP: Towards a data-driven knowledge discovery process for electronic social networks

Asamoah, D. A., & Sharda, R. (2019) · Journal of Decision System · doi:10.1080/12460125.2019.1696614 · Cited by 15

A review of data mining in knowledge management: applications/findings for transportation of small and medium enterprises

Selamat, S. A. M., Prakoonwit, S., & Khan, W. (2020) · SN Applied Sciences · doi:10.1007/s42452-020-2589-3 · Cited by 13

Data Mining for Small and Medium Enterprises: A Conceptual Model for Adaptation

Saeed, T. (2020) · Intelligent Information Management · doi:10.4236/iim.2020.125011 · Cited by 13

Agriculture data visualization and analysis using data mining techniques: application of unsupervised machine learning

Badapanda, K., Mishra, D. P., & Salkuti, S. R. (2022) · TELKOMNIKA (Telecommunication Computing Electronics and Control) · doi:10.12928/telkomnika.v20i1.18938 · Cited by 13

A Spectrum of Big Data Applications for Data Analytics

Chauhan, R., & Kaur, H. (2015) · Adaptation, learning, and optimization · doi:10.1007/978-3-319-16598-1_7 · Cited by 13

Applying data mining techniques for spatial distribution analysis of plant species co-occurrences

da Silva, L. A. E., de Siqueira, M. F., Pinto, F., Barros, F. S. M., Zimbrão, G., & de Souza, J. M. (2015) · Expert Systems with Applications · doi:10.1016/j.eswa.2015.08.031 · Cited by 13

Big Data Classification using Fuzzy K-Nearest Neighbor

El, M., Safwat, S., & Hegazy, O. (2015) · International Journal of Computer Applications · doi:10.5120/ijca2015907591 · Cited by 13

Exhaustive search algorithms to mine subgroups on Big Data using Apache Spark

Padillo, F., Luna, J. M., & Ventura, S. (2017) · Progress in Artificial Intelligence · doi:10.1007/s13748-017-0112-x · Cited by 13

Big Search in Cyberspace

Fang, B., Jia, Y., Li, X., Li, A., & Wu, X. (2017) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2017.2699675 · Cited by 13

Big Earth Data: a comprehensive analysis of visualization analytics issues

Merritt, P., Bi, H., Davis, B. M., Windmill, C., & Xue, Y. (2018) · Big Earth Data · doi:10.1080/20964471.2019.1576260 · Cited by 13

PTML Model of ChEMBL Compounds Assays for Vitamin Derivatives

Santana, R., Zuluaga, R., Gañán, P. F., Arrasate, S., Onieva, E., & González‐Díaz, H. (2020) · ACS Combinatorial Science · doi:10.1021/acscombsci.9b00166 · Cited by 13

A novel Gait-Appearance-based Multi-Scale Video Covariance Approach for pedestrian (re)-identification

Hadjkacem, B., Ayedi, W., Ayed, M. B., Alshaya, S. A., & Abid, M. (2020) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2020.103566 · Cited by 13

Building Technology and Predictive Analytics Models in the SAP Analytic Cloud Digital Service

Nazarov, D. M., Назаров, А., & Ковтун, Д. (2020) · IEEE Conference on Business Informatics · doi:10.1109/cbi49978.2020.10067 · Cited by 13

Online Streaming Feature Selection Based on Feature Interaction

Lv, Y., Lin, Y., Chen, X., Wang, D., & Wang, C. (2020) · IEEE International Conference on Knowledge Graph (ICKG) · doi:10.1109/icbk50248.2020.00017 · Cited by 13

Big Data Security

Benjelloun, F.-Z., & Lahcen, A. A. (2018) · IGI Global eBooks · doi:10.4018/978-1-5225-7501-6.ch003 · Cited by 13

Energy Oriented Concepts and Other SMART WORLD Trends as Game Changers of Co-Production—Reality or Future?

Adamik, A., Nowicki, M., & Puksas, A. (2022) · Energies · doi:10.3390/en15114112 · Cited by 14

Survey Big Data Analytics, Applications and Privacy Concerns

Puri, G. D., & Haritha, D. S. N. (2016) · Indian Journal of Science and Technology · doi:10.17485/ijst/2016/v9i17/93028 · Cited by 13

Data mining techniques for IoT and big data — A survey

Shobanadevi, A., & Maragatham, G. (2017) · International Conference on Intelligent Sustainable Systems (ICISS) · doi:10.1109/iss1.2017.8389260 · Cited by 13

DAPR-tree: a distributed spatial data indexing scheme with data access patterns to support Digital Earth initiatives

Xia, J., Huang, S., Zhang, S., Li, X., Lyu, J., Xiu, W., & Tu, W. (2020) · International Journal of Digital Earth · doi:10.1080/17538947.2020.1778804 · Cited by 13

Combining complex networks and data mining: why and howPreprint

Zanin, M., Papo, D., Sousa, P., Menasalvas, E., Nicchi, A., Kubik, E., & Boccaletti, S. (2016) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/054064 · Cited by 13

A Novel Approach to Increase the Efficiency of Filter-Based Feature Selection Methods in High-Dimensional Datasets With Strong Correlation Structure

Akoğul, S. (2023) · IEEE Access · doi:10.1109/access.2023.3325331 · Cited by 12

A Novel Three-Way Deep Learning Approach for Multigranularity Fuzzy Association Analysis of Time Series Data

Jiang, C., & Duan, Y. (2023) · IEEE Transactions on Fuzzy Systems · doi:10.1109/tfuzz.2023.3332921 · Cited by 12

All‐nonlinear static‐dynamic neural networks versus Bayesian machine learning for data‐driven modelling of chemical processes

Mukherjee, A., Adeyemo, S., & Bhattacharyya, D. (2024) · The Canadian Journal of Chemical Engineering · doi:10.1002/cjce.25379 · Cited by 12

Big data analysis using Hadoop cluster

Saldhi, A., Yadav, D., Saksena, D., Goel, A., Saldhi, A., & Indu, S. (2014) · IEEE International Conference on Computational Intelligence and Computing Research (ICCIC) · doi:10.1109/iccic.2014.7238418 · Cited by 12

A Survey on Big Data, Mining: (Tools, Techniques, Applications and Notable Uses)

Oweis, N. E., Owais, S. S. J., George, W., Suliman, M. G., & Snåšel, V. (2015) · Advances in intelligent systems and computing · doi:10.1007/978-3-319-21206-7_10 · Cited by 12

Relational Network for Knowledge Discovery through Heterogeneous Biomedical and Clinical Features

Chen, H., Chen, W., Liu, C., Zhang, L., Su, J., & Zhou, X. (2016) · Scientific Reports · doi:10.1038/srep29915 · Cited by 13

Different analytical techniques for big data analysis: A review

Narayanan, U., Paul, V., & Joseph, S. (2017) · International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS) · doi:10.1109/icecds.2017.8390139 · Cited by 12

Tensor-based Big Biometric Data Reduction in Cloud

Feng, J., Yang, L. T., & Zhang, R. (2018) · IEEE Cloud Computing · doi:10.1109/mcc.2018.043221013 · Cited by 12

Opinion Mining Summarization and Automation Process: A Survey

Khan, S. N., Nawi, N. M., Imrona, M., Shahzad, A., Ullah, A., & Rahman, A. (2018) · International Journal on Advanced Science Engineering and Information Technology · doi:10.18517/ijaseit.8.5.5002 · Cited by 12

Big Data, What Is It, Its Limits and Implications in Contemporary Life

KARAOULANIS, A. (2018) · Business Ethics and Leadership · doi:10.21272/bel.2(4).108-114.2018 · Cited by 12

Distributed Signal Recovery Based on In-network Subspace Projections

Lorenzo, P. D., Barbarossa, S., & Sardellitti, S. (2019) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2019.8682719 · Cited by 12

Research and Application of Element Logging Intelligent Identification Model Based on Data Mining

Liang, H., Chen, Y., Kan, M. J., & Gao, J. (2019) · IEEE Access · doi:10.1109/access.2019.2928001 · Cited by 12

A Study on the Application of Big Data Mining in e-Commerce

Zhao, X. (2018) · IEEE International Conference on Computer and Communications (ICCC) · doi:10.1109/compcomm.2018.8780856 · Cited by 12

Extracting Flooded Roads by Fusing GPS Trajectories and Road Network

She, S., Zhong, H., Fang, Z., Zheng, M., & Zhou, Y. (2019) · ISPRS International Journal of Geo-Information · doi:10.3390/ijgi8090407 · Cited by 12

Making AdaBoost Less Prone to Overfitting on Noisy Datasets

Modarres, Z. G., Shabankhah, M., & Kamandi, A. (2020) · International Conference on Web Research (ICWR) · doi:10.1109/icwr49608.2020.9122292 · Cited by 12

Internet of Things Based Wireless Garbage Monitoring System

Yanglu, Yadav, A., & Khan, A. (2019) · International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC) · doi:10.1109/i-smac47947.2019.9032540 · Cited by 12

Analysis and mathematical modeling of big data processing

Imanbaev, K. S., Синчев, Б. К., Sibanbayeva, S., Mukhanova, A., Nurgulzhanova, A. N., Zaurbekov, N., Zaurbekova, N., Korolyova, N. V., & Baibolova, L. K. (2020) · Peer-to-Peer Networking and Applications · doi:10.1007/s12083-020-00978-3 · Cited by 12

Hybrid Decision Tree for Machine Learning: A Big Data Perspective

Jena, M., Behera, R. K., & Dehuri, S. (2022) · Intelligent systems reference library · doi:10.1007/978-981-16-8930-7_9 · Cited by 13

Speech and music separation approaches - a survey

Mirbeygi, M., Mahabadi, A., & Ranjbar, A. (2022) · Multimedia Tools and Applications · doi:10.1007/s11042-022-11994-1 · Cited by 13

Semi-Supervised Graph Pattern Matching and Rematching for Expert Community Location

Li, L., Yan, M., Tao, Z., Chen, H., & Wu, X. (2022) · ACM Transactions on Knowledge Discovery from Data · doi:10.1145/3532623 · Cited by 12

Applications of Big Data in Media Organizations

Veglis, A. A., Saridou, T. A., Panagiotidis, K., Karypidou, C., & Kotenidis, E. (2022) · Social Sciences · doi:10.3390/socsci11090414 · Cited by 15

Review on Data Mining Techniques with Big Data

Babu, T. N., & Devi, R. M. (2015) · International Journal of Computer Engineering in Research Trends

Data Mining with Big Data Revolution Hybrid

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