Evolutionary computation for solving search-based data analytics problems

Cheng, Shi1; Ma, Lianbo2; Lu, Hui3; Lei, Xiujuan1; Shi, Yuhui4

2020-08

10.1007/s10462-020-09882-x

ARTIFICIAL INTELLIGENCE REVIEW   影响因子和分区

0269-2821

1573-7462

Automatic extracting of knowledge from massive data samples, i.e., big data analytics (BDA), has emerged as a vital task in almost all scientific research fields. The BDA problems are rather difficult to solve due to their large-scale, high-dimensional, and dynamic properties, while the problems with small data are usually hard to handle due to insufficient data samples and incomplete information. Such difficulties lead to the search-based data analytics problem, where a data analysis task is modeled as a complex, dynamic, and computationally expensive optimization problem and then solved by using an iterative algorithm. In this paper, we intend to present an extensive and in-depth discussion on the utilizing of evolutionary computation (EC) based optimization methods [including evolutionary algorithms (EAs) and swarm intelligence (SI)] for solving search-based data analysis problems. Then, as an example for illustration, we provide a comprehensive review of the applications of state-of-the-art EC methods for different types of data mining problems in bioinformatics. Here, the detailed analysis and discussion are conducted on three types of data samples, which include sequences data, network data, and image data. Finally, we survey the challenges faced by EC methods and the trend for future directions. Based on the applications of EC methods for search-based data analysis problems involving inexact and uncertain information, the insights of data analytics are able to understand better, and more efficient algorithms could be designed to solve real-world complex BDA problems.

Unified swarm intelligence Data analytics Evolutionary algorithms Search-based data analytics Swarm intelligence

SCI ; EI

英语

其他

National Natural Science Foundation of China[61806119][61672334][61761136008][61773103] ; Natural Science Basic Research Plan In Shaanxi Province of China[2019JM-320] ; Fundamental Research Funds for the Central Universities[GK202003078]

Computer Science

Computer Science, Artificial Intelligence

WOS:000554454900001

SPRINGER

COMPUTER SCIENCE

Web of Science

1.Shaanxi Normal Univ, Sch Comp Sci, Xian 710119, Peoples R China
2.Northeastern Univ, Coll Software, Shenyang 110819, Peoples R China
3.Beihang Univ, Sch Elect & Informat Engn, Beijing 100191, Peoples R China
4.Southern Univ Sci & Technol, Dept Comp Sci & Engn, Shenzhen Key Lab Computat Intelligence, Shenzhen 518055, Peoples R China

Cheng, Shi,Ma, Lianbo,Lu, Hui,et al. Evolutionary computation for solving search-based data analytics problems[J]. ARTIFICIAL INTELLIGENCE REVIEW,2020.

Cheng, Shi,Ma, Lianbo,Lu, Hui,Lei, Xiujuan,&Shi, Yuhui.(2020).Evolutionary computation for solving search-based data analytics problems.ARTIFICIAL INTELLIGENCE REVIEW.

Cheng, Shi,et al."Evolutionary computation for solving search-based data analytics problems".ARTIFICIAL INTELLIGENCE REVIEW (2020).