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- W3023525013 startingPage "103625" @default.
- W3023525013 abstract "Over the last few years, Big Data has gained a tremendous attention from the research community. The data being generated in huge quantity from almost every field is unstructured and unprocessed. Extracting knowledge base and useful information from the big raw data is one of the major challenges, present today. Various computational intelligence and soft computing techniques have been proposed for efficient big data analytics. Fuzzy techniques are one of the soft computing approaches which can play a very crucial role in current big data challenges by pre-processing and reconstructing data. There is a wide spread application domains where traditional fuzzy sets (type-1 fuzzy sets) and higher order fuzzy sets (type-2 fuzzy sets) have shown remarkable outcomes. Although, this research domain of “fuzzy techniques in Big Data” is gaining some attention, there is a strong need for a motivation to encourage researchers to explore more in this area. In this paper, we have conducted bibliometric study on recent development in the field of “fuzzy techniques in big data”. In bibliometric study, various performance metrics including total papers, total citations, and citation per paper are calculated. Further, top 10 of most productive and highly cited authors, discipline, source journals, countries, institutions, and highly influential papers are also evaluated. Later, a comparative analysis is performed on the fuzzy techniques in big data after analysing the most influential works in this field." @default.
- W3023525013 created "2020-05-13" @default.
- W3023525013 creator A5003623633 @default.
- W3023525013 creator A5028888771 @default.
- W3023525013 creator A5087542455 @default.
- W3023525013 date "2020-06-01" @default.
- W3023525013 modified "2023-10-07" @default.
- W3023525013 title "A bibliometric analysis and cutting-edge overview on fuzzy techniques in Big Data" @default.
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- W3023525013 doi "https://doi.org/10.1016/j.engappai.2020.103625" @default.
- W3023525013 hasPublicationYear "2020" @default.
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