Bibliometric survey of IT Infrastructure Management to Avoid Failure Conditions

Bhanage, Deepali Arun; Pawar, Ambika

doi:10.1108/idd-06-2020-0060

Cited by 8 publications

(5 citation statements)

References 17 publications

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“…Besides, the European and Asian countries mostly dominate the productivity. The USA ranks first in almost all areas of knowledge and the present study is in tune with the recent studies(Zurita et al, 2020;Loan and Yaseen, 2020;Bhanage and Pawar, 2021;and Mushtaq and Loan, 2021). However, China is competing neck to neck with the USA in cybersecurity research.…”

supporting

confidence: 91%

“…This study aims to identify the leading institutions over the past 25 years (1991–2015) and finds American universities as the most influential in Computer Science research. Bhanage and Pawar (2021 ) conducted a bibliometric study of articles on IT Infrastructure Management from articles accessed from Scopus. The study comes out with maximum publications of IT infrastructure management from conferences and journals.…”

Section: Review Of Literaturementioning

confidence: 99%

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Global research productivity in cybersecurity: a scientometric study

Loan

Bashir

Nasreen

2021

GKMC

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Purpose The purpose of the study is to conduct a scientometric analysis of cybersecurity literature indexed in the core collection of the Web of Science for a period of ten years (2011–2020). Design/methodology/approach Cybersecurity is a focused topic of research across the globe. To identify the global research productivity in the field, the terms “cybersecurity, cyber-security, web security, information security, computer security, etc.” were used for retrieving the publications in the advanced search mode of the database “Web of Science”, limiting the time frame for 2011– 2020. The results retrieved were downloaded in the Excel file for further analysis and interpretation. The harvested data was analysed by using scientometric techniques to measure the progress such as growth rate, doubling time and author collaborations. Besides, the Biblioshiny and VOSviewer software were used for mapping networks. Findings The research output in the field of cybersecurity has shown an increasing trend during 2011–2020, and the maximum number of scholarly publications was published in 2020 (1,581), i.e. more than 715% of 2011 (221). A good number of countries (93) have contributed globally in cybersecurity research, and the highest share in research publications was reported by the USA (23.55%), followed by China (23.24%), South Korea (5.31%), UK (5.28%) and India (4.25%). The authorship patterns in cybersecurity publications show a collaborative trend, as most articles have been published by multiple authors. Total 5,532 (90.14%) articles have been published in co-authorship, whereas only 605 (9.86%) articles have been published by single authors. Keyword analysis shows that the most common keyword research by the authors is cybersecurity and its variants such as “cyber security” and “cyber-security” (1,698) followed by security (782), computer security (680) and information security (329). Research limitations/implications The database studied for the work does not represent the total literary output available on the theme. There are plenty of other databases, such as Scopus, Compendex, INSPEC, IEEE Xplore, arXiv, contributing to the same theme as well. Practical implications The findings of the study may help researchers, information technologists, library professionals and information specialists to identify the research progress, authorship patterns, collaborative networks and hot topics of research in the field of cybersecurity. Besides, it will assess the global response to the cybersecurity issue. Originality/value The study is the scientometric analysis of the cybersecurity based on current literature and will highlight the progress and development of global research in the said field.

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confidence: 91%

Section: Review Of Literaturementioning

confidence: 99%

Global research productivity in cybersecurity: a scientometric study

Loan

Bashir

Nasreen

2021

GKMC

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“…IT infrastructure management is very important to avoid any machinery failure conditions. The papers relevant to this topic are analyzed with bibliometric parameters revealing anomaly detection, log analysis and learning systems as the most frequently used keywords (Bhanage and Pawar, 2021). Talan (2021) observed the status of the papers on AI applications in education with data extracted from WoS.…”

Section: Artificial Intelligence In Librariesmentioning

confidence: 99%

Mapping the literature on the application of artificial intelligence in libraries (AAIL): a scientometric analysis

Borgohain

Bhardwaj

Verma

2022

LHT

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PurposeArtificial Intelligence (AI) is an emerging technology and turned into a field of knowledge that has been consistently displacing technologies for a change in human life. It is applied in all spheres of life as reflected in the review of the literature section here. As applicable in the field of libraries too, this study scientifically mapped the papers on AAIL and analyze its growth, collaboration network, trending topics, or research hot spots to highlight the challenges and opportunities in adopting AI-based advancements in library systems and processes.Design/methodology/approachThe study was developed with a bibliometric approach, considering a decade, 2012 to 2021 for data extraction from a premier database, Scopus. The steps followed are (1) identification, selection of keywords, and forming the search strategy with the approval of a panel of computer scientists and librarians and (2) design and development of a perfect algorithm to verify these selected keywords in title-abstract-keywords of Scopus (3) Performing data processing in some state-of-the-art bibliometric visualization tools, Biblioshiny R and VOSviewer (4) discussing the findings for practical implications of the study and limitations.FindingsAs evident from several papers, not much research has been conducted on AI applications in libraries in comparison to topics like AI applications in cancer, health, medicine, education, and agriculture. As per the Price law, the growth pattern is exponential. The total number of papers relevant to the subject is 1462 (single and multi-authored) contributed by 5400 authors with 0.271 documents per author and around 4 authors per document. Papers occurred mostly in open-access journals. The productive journal is the Journal of Chemical Information and Modelling (NP = 63) while the highly consistent and impactful is the Journal of Machine Learning Research (z-index=63.58 and CPP = 56.17). In the case of authors, J Chen (z-index=28.86 and CPP = 43.75) is the most consistent and impactful author. At the country level, the USA has recorded the highest number of papers positioned at the center of the co-authorship network but at the institutional level, China takes the 1st position. The trending topics of research are machine learning, large dataset, deep learning, high-level languages, etc. The present information system has a high potential to improve if integrated with AI technologies.Practical implicationsThe number of scientific papers has increased over time. The evolution of themes like machine learning implicates AI as a broad field of knowledge that converges with other disciplines. The themes like large datasets imply that AI may be applied to analyze and interpret these data and support decision-making in public sector enterprises. Theme named high-level language emerged as a research hotspot which indicated that extensive research has been going on in this area to improve computer systems for facilitating the processing of data with high momentum. These implications are of high strategic worth for policymakers, library stakeholders, researchers and the government as a whole for decision-making.Originality/valueThe analysis of collaboration, prolific authors/journals using consistency factor and CPP, testing the relationship between consistency (z-index) and impact (h-index), using state-of-the-art network visualization and cluster analysis techniques make this study novel and differentiates it from the traditional bibliometric analysis. To the best of the author's knowledge, this work is the first attempt to comprehend the research streams and provide a holistic view of research on the application of AI in libraries. The insights obtained from this analysis are instrumental for both academics and practitioners.

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“…Moreover, a small failure in any of the infrastructure components gives rise to catastrophic failures accompanied by downtime [1]. Research [2] shows that these failures can lead to financial losses, reputational damage, and customer dissatisfaction. Thus, developing a system that can perform accurate and timely failure detection is paramount.…”

Section: Introductionmentioning

confidence: 99%

Robust Analysis of IT Infrastructure's Log Data with BERT Language Model

Bhanage¹,

Pawar²

2023

IJACSA

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Now-a-days, failure detection and prediction have become a significant research focus on enhancing the reliability and availability of IT infrastructure components. Log analysis is an emerging domain aimed at diminishing downtime caused by IT infrastructure components' failure. However, it can be challenging due to poor log quality and large data sizes. The proposed system automatically classifies logs based on log level and semantic analysis, allowing for a precise understanding of the meaning of log entries. Using the BERT pre-trained model, semantic vectors are generated for various IT infrastructures, such as Server Applications, Cloud Systems, Operating Systems, Supercomputers, and Mobile Systems. These vectors are then used to train machine learning (ML) classifiers for log categorization. The trained models are competent in classifying logs by comprehending the context of different types of logs. Additionally, semantic analysis outperforms sentiment analysis when dealing with unobserved log records. The proposed system significantly reduces engineers' day-to-day error-handling work by automating the log analysis process.

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Bibliometric survey of IT Infrastructure Management to Avoid Failure Conditions

Cited by 8 publications

References 17 publications

Global research productivity in cybersecurity: a scientometric study

Global research productivity in cybersecurity: a scientometric study

Mapping the literature on the application of artificial intelligence in libraries (AAIL): a scientometric analysis

Robust Analysis of IT Infrastructure's Log Data with BERT Language Model

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