A Study on the Developing of Big Data Services in Public Library

Pyo, Soon Hee; Kim, Yun Hyung; Kim, Hye Sun; Kim, Wan Jong

doi:10.3743/kosim.2015.32.2.063

Cited by 2 publications

(3 citation statements)

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“…The studies on analysis of log data in a library are those by Zhang and Wang (2013), Pyo et al (2015), Urbano et al (2015) and Choi et al (2018). First, Zhang and Wang (2013) implemented association rules to mine transactional data generated in the process of library service.…”

Section: Studies On Analysis Of Log Data In a Librarymentioning

confidence: 99%

“…Based on the result of the implementation, they aimed to provide accurate service for readers. Pyo et al (2015) examined the concept and content of big data in a library and analyzed its usage possibility based on the type. Consequently, they proposed a service model focusing on Decision Support Service for Librarians and Book Recommendation Service for Users.…”

Section: Studies On Analysis Of Log Data In a Librarymentioning

confidence: 99%

“…The studies in library and information science have been conducted mainly using observation and questionnaires. In the last decade, however, there were new attempts 680 LHT 38,3 regarding research methodology such as using log data analysis (Zhang and Wang, 2013;Pyo et al, 2015;Siguenza-Guzman et al, 2015;Choi et al, 2018) and GIS (Mandel, 2010;2016, Given andArchibald, 2015), with developed techniques. On the contrary, as access to digital resources and services increased and the users' activities in a library became different from the past, the study focusing on space in library to suite patrons' activities increased with worries about the library's future (Given and Archibald, 2015).…”

Section: Studies On Spaces In a Librarymentioning

confidence: 99%

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Spatial usage analysis based on user activity big data logs in library

Kim

Gang²,

Oh³

2019

LHT

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Purpose This study explored spatial usage of a public library based on activity logs produced by real users. The purpose of this paper is to provide preliminary data for decision-making when establishing the library operation policy. Design/methodology/approach To achieve the goal, the author collected a variety of data including 274,242 seat reservations logs, 3,361,284 collection usage logs, and 96,098 user information for the four years in which the National Library of Korea, Sejong actually operated. The crawled data were analyzed statistically in terms of demography, month, day of week, time of day and room by room. The author conducted additional in-depth analysis according to the external factors such as weather or social demographic environment. Finally, the author discussed several issues and verified feasibility of the proposals to support decision-making in operating a library in conclusion with a secondary librarian interview. Findings The usage rate in all the spaces of the National Library of Korea, Sejong, has been increasing since its opening, and, in particular, the usage rate increases sharply in January, February, July and August. In addition, the usage rate during weekends was higher than that during weekdays, and all the four spaces had a high usage rate during the afternoon. These results seem to be related to weather, users’ life pattern, users’ age, and position of PCs and seats. Based on the circulation logs analysis of children’s collections, users in their 10s and 40s showed the same space usage pattern. Originality/value This study has significance in that it attempted to analyze logs produced by real users during the actual library operation period, which has not been frequently attempted in the previous studies on libraries. The findings will be provided as basic data to support decision-making for efficient operation of libraries.

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Section: Studies On Analysis Of Log Data In a Librarymentioning

confidence: 99%

Section: Studies On Analysis Of Log Data In a Librarymentioning

confidence: 99%

Section: Studies On Spaces In a Librarymentioning

confidence: 99%

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Spatial usage analysis based on user activity big data logs in library

Kim

Gang²,

Oh³

2019

LHT

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Reform and Innovation of Government Public Service Algorithm Model in the Era of Big Data

2021

J. Phys.: Conf. Ser.

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With the continuous development of information technology, data is being generated and accumulated at an unprecedented speed. Big data policies have gradually extended from the overall plan to major industries and various sub-fields. The development of the industry has risen to the national strategic level. In order to provide big data Development provides a good environment. The government has issued relevant policies and regulations at the national level to conduct top-level design and system deployment of the national big data development strategy. The purpose of this article is to organically integrate public management with the advanced information technology of big data algorithms through interdisciplinary, and provide theoretical basis and technical support for the innovation of government public services in my country. To solve the difficulties and challenges encountered by government public service algorithms in the big data environment and the limitation of the problem scale of government public service algorithms under traditional platforms, the MapReduce model is used to transplant government public service algorithms to the Hadoop platform for research. The government public service model algorithm is MapReduce, and the algorithm of the government public service model under the Hadoop platform is analyzed experimentally from the solution quality and problem scale of the algorithm. The experiment shows that after transplanting the government public service model algorithm to the cloud computing platform, the price of the optimal solution for the public service is calculated to be 1,756,633,690 yuan/1,000 square meters.

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A Study on the Developing of Big Data Services in Public Library

Cited by 2 publications

References 0 publications

Spatial usage analysis based on user activity big data logs in library

Spatial usage analysis based on user activity big data logs in library

Reform and Innovation of Government Public Service Algorithm Model in the Era of Big Data

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