Quantitative and Qualitative Analysis of Time-Series Classification Using Deep Learning

Abstract

Time-series classification is utilized in a variety of applications leading to the development of many data mining techniques for time-series analysis. Among the broad range of time-series classification algorithms, recent studies are considering the impact of deep learning methods on time-series classification tasks. The quantity of related publications requires a bibliometric study to explore most prominent keywords, countries, sources and research clusters. The paper conducts a bibliometric analysis on related publications in time-series classification, adopted from Scopus database between 2010 and 2019. Through keywords cooccurrence analysis, a visual network structure of top keywords in time-series classification research has been produced and deep learning has been introduced as the most common topic by additional inquiry of the bibliography. The paper continues by exploring the publication trends of recent deep learning approaches for time-series classification. The annual number of publications, the productive and collaborative countries, the growth rate of sources, the most occurred keywords and the research collaborations are revealed from the bibliometric analysis within the study period. The research field has been broken down into three main categories as different frameworks of deep neural networks, different applications in remote sensing and also in signal processing for time-series classification tasks. The qualitative analysis highlights the categories of top citation rate papers by describing them in details. INDEX TERMS Time-series classification, deep learning, remote sensing, signal processing, bibliometrics, research productivity.

A Bibliometric Statistical Analysis of the Fuzzy Inference System - based Classifiers

“…In order to overcome the above mentioned multiple shortcomings [16], [21]- [23], [25], this section introduces the proposed systematic and time-saving bibliometric statistical analysis approach. The research objectives of proposing the new approach include: 1) ensure the analytical balance and coverage of all key types of bibliometric data; 2) ensure simplified analysis methods and good analytical standards to promote preliminary research and exploration; 3) ensure that the method can output good results and provide highquality features of a research topic.…”

“…The bibliometric software package in R Studio (an R tool for comprehensive scientific map analysis) [28] is designed for quantitative research in Scient metrics and Bibliometrics. The tool provides various routines to import bibliographic data from well-known databases such as SCO-PUS and WoS [23]. The Microsoft Office Excel functions can conveniently perform statistics, analysis, and graphing on complete publications' bibliometric information.…”

“…Although this study utilizes one convincing Query to collect full publications from two well-known databases, this method may force other researchers with insufficient knowledge of his research topic or do not understand any bibliometric analysis methods to spend more time discussing the necessary high-cited papers for conducting Query. Some papers could provide different methods for expanding keywords to obtain one sufficiently convincing Query for collecting publications, such as [16], [21]- [23], [25]. In addition to the statistics and analysis of the necessary bibliometric information of publications, although this study expands the range of the top-ranked collections from the top 10 in regular numbers to the Top 20, they still cannot stand for the research topic of [30], visibility may be an essential factor in increasing the citation number.…”

“…It was also shown that peer-reviewed high-impact journals and academic databases could provide helpful and reliable research information. Reference [23] relied on a mixed-method, including bibliometric analysis and traditional review analysis, to complete quantitative and qualitative analysis. Although the above current research provided various bibliographic analysis methods, the low-quality trade-off between various bibliographic information and the lack of some critical bibliographic information is still apparent.…”

“…Besides, because of the different focuses of their bibliographic statistical analysis approaches, it is difficult to determine which one is better than others. In particular, the research [23] may confuse us whether the bibliometric statistical analysis lacks research value, and the survey papers still have to rely on traditional survey approach to make up for its shortcomings.…”