Table 4 List of highly cited papers

Trends in big data analytics

Kambatla et al.

[50]

Big data: a survey

Chen et al.

[6]

A comparison of parallel large-scale knowledge acquisition using rough set theory on different MapReduce runtime systems

Zhang et al.

[51]

A scalable two-phase top-down specialization approach for data anonymization using MapReduce on cloud

Zhang et al.

[52]

Data mining with big data

Wu et al.

[1]

Comparative experiments using supervised learning and machine translation for multilingual sentiment analysis

Balahur and Turchi

[53]

Techniques and applications for sentiment analysis

Feldman

[54]

New avenues in opinion mining and sentiment analysis

Cambria et al.

[55]

Review of performance metrics for green data centers: a taxonomy study

Wang and Khan

[56]

G-Hadoop: MapReduce across distributed data centers for data-intensive computing

Wang et al.

[57]

Data center network virtualization: a survey

Bari et al.

[58]

Business intelligence and analytics: from big data to big impact

Chen et al.

[59]

Energy-aware resource allocation heuristics for efficient management of data centers for cloud computing

Beloglazov et al.

[60]

A survey on optical interconnects for data centers

Kachris and Tomkos

[61]

Scikit-learn: machine learning in python

Pedregosa et al.

[62]

Lexicon-based methods for sentiment analysis

Taboada et al.

[63]

MapReduce: a flexible data processing tool

Dean and Ghemawat

[64]

Faster and better: a machine learning approach to corner detection

Rosten et al.

[65]

VL2: a scalable and flexible data center network

Greenberg et al.

[66]

A study of statistical techniques and performance measures for genetics-based machine learning: accuracy and interpretability

Garcia et al.

[67]

Improving the performance of predictive process modeling for large datasets

Finley et al.

[68]

CloudBurst: highly sensitive read mapping with MapReduce

Schatz

[69]

A scalable, commodity data center network architecture

Al-Fares et al.

[70]

MapReduce: simplified data processing on large clusters

Dean and Ghemawat

[71]

Analysis of interpretability-accuracy tradeoff of fuzzy systems by multiobjective fuzzy genetics-based machine learning

Ishibuchi and Nojima

[72]

A machine learning information retrieval approach to protein fold recognition

Cheng and Baldi

[73]

Machine learning for high-speed corner detection

Rosten and Drummond

[74]

Predicting subcellular localization of proteins using machine-learned classifiers

Lu et al.

[75]