Item history (bjohas, Thu Jan 18 2024 22:08:48 GMT+0000 (GMT))

TY - JOUR
TI - Text classification using deep learning techniques: a bibliometric analysis and future research directions
AU - Sarin, Gaurav
AU - Kumar, Pradeep
AU - Mukund, M.
T2 - Benchmarking: An International Journal
DA - 2023///
PY - 2023
DO - 10.1108/BIJ-07-2022-0454
DP - Google Scholar
ST - Text classification using deep learning techniques
UR - https://www.emerald.com/insight/content/doi/10.1108/BIJ-07-2022-0454/full/html
Y2 - 2023/11/28/12:34:24
KW - _TBC for use in LR
ER -

TY - JOUR
TI - Text classification using deep learning techniques: a bibliometric analysis and future research directions
AU - Sarin, Gaurav
AU - Kumar, Pradeep
AU - Mukund, M.
T2 - Benchmarking: An International Journal
AB - Purpose Text classification is a widely accepted and adopted technique in organizations to mine and analyze unstructured and semi-structured data. With advancement of technological computing, deep learning has become more popular among academicians and professionals to perform mining and analytical operations. In this work, the authors study the research carried out in field of text classification using deep learning techniques to identify gaps and opportunities for doing research. Design/methodology/approach The authors adopted bibliometric-based approach in conjunction with visualization techniques to uncover new insights and findings. The authors collected data of two decades from Scopus global database to perform this study. The authors discuss business applications of deep learning techniques for text classification. Findings The study provides overview of various publication sources in field of text classification and deep learning together. The study also presents list of prominent authors and their countries working in this field. The authors also presented list of most cited articles based on citations and country of research. Various visualization techniques such as word cloud, network diagram and thematic map were used to identify collaboration network. Originality/value The study performed in this paper helped to understand research gaps that is original contribution to body of literature. To best of the authors' knowledge, in-depth study in the field of text classification and deep learning has not been performed in detail. The study provides high value to scholars and professionals by providing them opportunities of research in this area.
DA - 2023/01/01/
PY - 2023
DO - 10.1108/BIJ-07-2022-0454
DP - Emerald Insight
VL - ahead-of-print
IS - ahead-of-print
SN - 1463-5771
ST - Text classification using deep learning techniques
UR - https://doi.org/10.1108/BIJ-07-2022-0454
Y2 - 2024/01/18/22:08:34
L1 - https://www.emerald.com/insight/content/doi/10.1108/BIJ-07-2022-0454/full/pdf?title=text-classification-using-deep-learning-techniques-a-bibliometric-analysis-and-future-research-directions
KW - Bibliometric analysis
KW - Classification
KW - Data mining
KW - Deep learning
KW - Text analytics
ER -

group: 2486141

itemKey: J6KNBKMH

itemKeyOld: KMNV7QKL

item.extra: Publisher: Emerald Publishing Limited

itemOLD.extra: