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Handwritten character recognition serves as a key element in improving human–computer interaction and document digitization. This paper presents a bibliometric analysis of 134 documents in the Web of Science database related to Hindi (Devanagari) character and word recognition and analyzes the historical development, existing condition, and possible growth trend in this research area. A methodical approach is used to collect the data on Hindi character recognition in the Web of Science database from 2000 to 2023. A discussion related to the publications, citations, and predictions of the pertinent documents is presented. Tableau 2022, Excel, and VOSviewer 1.6.18 visualization tools are used for visual analysis. Finding the most well-known and significant writers, sources, publications, nations, and organizations is the goal of this study. Document selection criteria are well stated for citation analysis and ranking. To find the hotspots and development trends, text data content analysis, author keywords, and index keywords are used. This study will help the researchers increase their understanding and swiftly grasp the status and pattern of development.

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WoS Bibliometric and Content Analysis on Handwritten Hindi Characters Recognition

  • 会议论文

  • 发表日期：

    2025年

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  • Mahadev,
  • Dayal Chandra Sati,
  • Madan Lal Saini

摘要

Handwritten character recognition serves as a key element in improving human–computer interaction and document digitization. This paper presents a bibliometric analysis of 134 documents in the Web of Science database related to Hindi (Devanagari) character and word recognition and analyzes the historical development, existing condition, and possible growth trend in this research area. A methodical approach is used to collect the data on Hindi character recognition in the Web of Science database from 2000 to 2023. A discussion related to the publications, citations, and predictions of the pertinent documents is presented. Tableau 2022, Excel, and VOSviewer 1.6.18 visualization tools are used for visual analysis. Finding the most well-known and significant writers, sources, publications, nations, and organizations is the goal of this study. Document selection criteria are well stated for citation analysis and ranking. To find the hotspots and development trends, text data content analysis, author keywords, and index keywords are used. This study will help the researchers increase their understanding and swiftly grasp the status and pattern of development.