CALIBER 2022: Varanasi, UP

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https://ir7.inflibnet.ac.in/handle/1944/2357

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Browsing CALIBER 2022: Varanasi, UP by Subject "Bibliometrics"

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    Global Retracted Research Publications: A Bibliometric Study
    (INFLIBNET Centre, Gandhinagar, 2022-11) Garg, Mohit; Hasan, Nabi
    The present study used a bibliometric technique to draw the patterns in retracted publications over time. A sample of bibliographic data of 12876 documents up to the year 2021 was extracted from the Scopus database. The analysis found that the number of retracted documents has significantly increased in the last decade, with most documents in 2010 (4377) followed by 2011 (3534). The study found that most retracted documents were from China, followed by the United States and India. The highest number of 70 retracted documents were from the author Nazari, A. of Islamic Azad University, Iran, with a rate of 4.04 retractions per total document published. The other authors were Ueshima, H. (68), Otake, H. (45), Sato, Y. (45), and Iwamoto, J. (41) from Japanese Institutions. The highest rate of retraction per total documents were of Ghoranneviss, M., Islamic Azad University, Iran (24.65), followed by Boldt, J., Justus-Liebig-Universität Gießen (24.04), and Shamshirband, S. National Yunlin University of Science and Technology, Taiwan (18.54). The majority of the source type was found to be Conference Proceedings (11096, 60.71%), followed by Journal Publications (7159, 39.17%). The study found the maximum number of retracted publications were in the Conference Proceedings (11096, 60.71%), followed by Journals (7159, 39.17%).
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    Knowledge Management: A Bibliometric Analysis
    (INFLIBNET Centre, Gandhinagar, 2022-11) Joseph, Jobin
    Knowledge management has acquired great importance in this information overloaded situation. Every organization or institution in these days gives utmost priority to knowledge management. Because any organization or institution would be useful and persuasive if and only if it caters the information needs of patrons and society in general. A good knowledge management system is a must to cater the information need of the society. A good, efficient knowledge management system can play a vital role in enhancing the dissemination and retrieval of the information. Besides, it save the time and resources to a great extent. This forced the academic world to concentrate more on the theme knowledge management. Many authors studied and written on this theme further and discussed it from different point of views with a view to paving the way to function better and satisfy the information needs. This article makes a bibliometric analysis of the paper written on the theme knowledge management in order to find the research trends on this theme.
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    Towards Advancing Creativity in Libraries Using Natural Language Processing for Data Curation: A Bibliometric Analysis
    (INFLIBNET Centre, Gandhinagar, 2022-11) Rana, Pooja; Singh, Pramod Kumar
    Natural language processing has significantly become one of the most advancing topics in the field of artificial intelligence. Knowing its capabilities of using semantics to extract relevant information from large volumes of data, its applications for data curation are worth exploring. NLP has an increasingly signifying role in different fields; therefore this study aims to examine the research output of the NLP for data curation. For this purpose, a bibliometric study on NLP for data curation is presented and research publications are retrieved from Scopus Database. The network analysis is done using the VOSviewer software. The results have shown an increase in the publication from the year 2014-2021 with an average of 29-30 publications each year. The USA is found to be dominating the field among other countries. Among the most prolific authors,Ananiadou, Vijay-Shanker, and Hirschman lead the list, accounting for 7.63% of the total output. The five main thematic areas identified are natural language processing, human, information processing, information retrieval, and data mining. The bibliometric analysis of NLP for data curation, uncovering the present status, paves the way for future research opportunities in libraries.This study will allow us to explore and understand research developments systematically and optimize libraries by employing NLP models for data curation for effective transmission of data for the end users.