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- P-ISSN1013-0799
- E-ISSN2586-2073
- KCI
Vol.34 No.4
Abstract
Recently, deep learning has been rapidly spreading as an innovative machine learning technique in various domains. This study explored the research trends of deep learning via modified ego centered topic citation analysis. To do that, a few seed documents were selected from among the retrieved documents with the keyword ‘deep learning’ from Web of Science, and the related documents were obtained through citation relations. Those papers citing seed documents were set as ego documents reflecting current research in the field of deep learning. Preliminary studies cited frequently in the ego documents were set as the citation identity documents that represents the specific themes in the field of deep learning. For ego documents which are the result of current research activities, some quantitative analysis methods including co-authorship network analysis were performed to identify major countries and research institutes. For the citation identity documents, co-citation analysis was conducted, and key literatures and key research themes were identified by investigating the citation image keywords, which are major keywords those citing the citation identity document clusters. Finally, we proposed and measured the citation growth index which reflects the growth trend of the citation influence on a specific topic, and showed the changes in the leading research themes in the field of deep learning.
Abstract
This study aims to introduce an emerging prescriptive analytics method and suggest its efficient application to a category-based service system. Prescriptive analytics method provides the whole process of analysis and available alternatives as well as the results of analysis. To simulate the process of optimization, large scale journal articles have been collected and categorized by classification scheme. In the process of applying the concept of prescriptive analytics to a real system, we have fused a dynamic automatic-categorization method for large scale documents and intellectual structure analysis method for scholarly subject fields. The test result shows that some optimized scenarios can be generated efficiently and utilized effectively for reorganizing the classification-based service system.
Abstract
This study analyzed the type, subject and open level of research data in the field of library and information science field shared by Figshare, and statistically analyzed the characteristics of data with relatively high recyclability. The results of the analysis showed that datasets and papers were most common data types, and open access and research data were the most common keywords of data, and that 70% of the data were published in a form that can not be processed mechanically such as pdf. As a result of analysis of the relationship between characteristics of research data and degree of sharing, open access areas such as APC (Article Processing Charge) were found to be most common in the subject. However in data type, gray literature such as paper found to be highly utilized rather than dataset.
Abstract
Technical documents are important research outputs generated by knowledge and information society. In order to properly use the technical documents properly, it is necessary to utilize advanced information processing techniques, such as summarization and information extraction. In this paper, to extract core information, we automatically extracted the terminologies and their definition based on definitional sentences patterns and the structure of technical documents. Based on this, we proposed the system to build a specialized terminology dictionary. And further we suggested the personalized services so that users can utilize the terminology dictionary in various ways as an knowledge memory. The results of this study will allow users to find up-to-date information faster and easier. In addition, providing a personalized terminology dictionary to users can maximize the value, usability, and retrieval efficiency of the dictionary.
Abstract
Data Science is emerging as a closely related field of study to Library and Information Science (LIS), and as an interdisciplinary subject combining LIS, statistics and computer science in an attempt to understand the value of data by applying what LIS has been doing for collecting, storing, organizing, analyzing, and utilizing information. To investigate which subject fields other than LIS, statistics, and computer science are related to Data Science, this study retrieved 667 materials from Web of Science Core Collection, extracted terms representing Web of Science Categories, examined subject fields that are studying Data Science using descriptive analysis, analyzed the intellectual structure of the field by co-word analysis and network analysis, and visualized the results as a Pathfinder network with clustering created with the PNNC clustering algorithm. The result of this study might help to understand the intellectual structure of the Data Science field, and may be helpful to give an idea for developing relatively new curriculum.
Abstract
RFID technology that is one of the ways to enhance productivity and competitiveness across diverse sectors of IT, is being hailed as a technology that replaces the bar code system and brings more convenience to the system. RFID system have been already applied to libraries, and archive, and is expected to bring advancements in the development of more effective records management systems. However, the system is still in the initial stage of the introduction, and it has been difficult to introduction because of trivial problems and unsafe elements, and studies have not been conducted to identify the detailed problems of the system. So, In this study, conducted interviews and surveys of executives of archive who operate the RFID based records management system. Based on this, we found the operational status of the RFID based records management system operating in the current archive, and the problems in the RFID based records management system. In conclusion, we suggest improvements in efficient operation methods.
Abstract
Many readers tend to read books of a specific author and to expand their reading areas according to the author. This study chose Edgar Allan Poe and analyzed the image of the author using co-recommended authors and books by other readers. The frequencies of co-occurred authors and books were investigated and the relations of authors and books were analyzed with network analysis methods. As a result, genre images of Poe, related authors, and related books are discovered. This study also suggested the methods to identify the image of a author, related author groups, and related books for libraries’ reading programs and book curation.
Abstract
Evaluation of education and training is the act of measuring and observing contents related to an educational program and evaluating its quality; and thereby providing the basis for the changes in the curriculum. The National Library of Korea (NLK) has urgently needed to introduce an evaluation method that can enhance the performance and quality of its continuing education program. Therefore, this study is aimed at developing an evaluation model that can objectively and comprehensively measure the effectiveness of NLK’s job training program for its librarians. To this end, the study applied Kirkpatrick’s 4-Level Training Evaluation Model and conducted review of preceding researches, investigation of NLK’s librarian continuing education program, along with analysis on the stakeholders’ needs. Based on the results, the study suggested evaluation system to establish the directions of the evaluation system. The findings of this study are expected to be used as a practical evaluation system for NLK’s librarian education program.
Abstract
In this study, based on the analysis of FRBRoo, we tried to propose suggestions to expand and improve the FRBR family conceptual model. FRBRoo is a plug-in ontology of CIDOC CRM with cooperation of museum field. As FRBR family models also revised and integrated into IFLA Library Reference Model, the additional analysis on IFLA LRM was performed. If bibliographic information is required to support the technical and user services of the library, the way to analyze the bibliographic information should be improved in order to cope with the new challenges faced by the library. To do this, time-related event concepts should be reflected in the modeling of bibliographic information. It is also necessary to expand the creation and exchange unit of bibliographic information to smaller units or larger units than legacy bibliographic records. Using FRBRoo as a linkage tool for the sharing of bibliographic information is also suggested.
Abstract
This study mainly investigates the motivations of YouTube and Flicker users for posting videos or images/photos on each service. The motivational framework with ten factors such as enjoyment, self-efficacy, learning, personal gain, altruism, empathy, social engagement, community interest, reputation and reciprocity were used to test the motivations. Those who are users of YouTube and Flickr were recruited from Amazon Mechanical Turk to participate in online surveys. Findings show that learning and social engagement are the two most highly rated motivations. Altruism was rated relatively low, although it was strongly correlated with all other motivations. Personal gain was rated as the lowest by both users but Flickr users rated personal gain higher than YouTube users. Findings from this study could be applicable to specify user motivations for using the services and to upgrade the designs of the services in the future.
Abstract
Digital curation which maintains digital information over time and adds value becomes, nowadays, one of the important business process in the special libraries. This study is to investigate the business practice level of the digital curation in the special libraries and the librarians’ perception on the importancy of digital curation. In results, it is found that most librarian, in general, think that the level of digital curation practice in the special libraries is insufficiency. Also, the study finds that the librarians of special libraries have difficulties in terms of the lack of willingness and funding problems as well as the lack of long-term policies and suitable business procedures; they only focus the cycle of information organization-information storage-information use among the 8 processes of digital curation; they need to recognize the importance of digital preservation as one of the essential process of digital curation and make effort to extend technological capacity of digital preservation.
Abstract
This paper aims to develop an evaluation model for library mobile services in terms of service quality. First, a literature review of the service quality evaluation model and the mobile library service evaluation was conducted. Then, based on the analysis, the evaluation model consisting of 4 quality dimensions, 10 quality factors, 39 quality measurement items was developed. Delphi method was applied to verify the validity of the model. Finally, a final model consisting of 4 quality dimensions, 9 quality factors, and 37 quality measurement items was derived. The evaluation model proposed in this study can be used as a measure of library mobile service quality and can be used as a guideline for improvement of library mobile service.
Abstract
This study aims to analyze the current status of records management in local broadcasting stations. To that end, it conducted interviews with personnels in charge of keeping records in KBS in J province, MBC in J province, and 2 local commercial broadcasting stations as well as KBS headquarter. The findings show that the local broadcasting stations keep digital files of born-digital broadcast records in a server in a relatively systematic way. However, they never digitalized their analog records and do not even know the exact volume of total records they own. In addition, they have significant difficulties in preserving and utilizing broadcast records because of outdated preservation facilities and information retrieval systems. Based on the findings, this study suggests ways to improve current broadcast record management such as preparation of record management guidelines, construction of an inventory for owned records, digitalization initiative, and provision of metadata education for PDs, etc.
Abstract
Research on automatic classification of records and documents has been conducted for a long time. Recently, artificial intelligence technology has been developed to combine machine learning and deep learning. In this study, we first looked at the process of automatic classification of documents and learning method of artificial intelligence. We also discussed the necessity of applying artificial intelligence technology to records management using various cases of machine learning, especially supervised methods. And we conducted a test to automatically classify the public records of the Seoul metropolitan government into BRM using ETRI’s Exobrain, based on supervised machine learning method. Through this, we have drawn up issues to be considered in each step in records management agencies to automatically classify the records into various classification schemes.