• Journal of the Korean Society for information Management
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• v.37 no.1
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• pp.1-21
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• 2020

This study applied automatic classification using table of contents (TOC) text for 6,253 social science books from a newly arrived list collected by a university library. The k-nearest neighbors (kNN) algorithm was used as a classifier, and the ten divisions on the second level of the DDC's main class 300 given to books by the library were used as classes (labels). The features used in this study were keywords extracted from titles and TOCs of the books. The TOCs were obtained through the OpenAPI from an Internet bookstore. As a result, it was found that the TOC features were good for improving both classification recall and precision. The TOC was shown to reduce the overfitting problem of imbalanced data with its rich features. Law and education have high topic specificity in the field of social sciences, so the only title features can bring good classification performance in these fields.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.27 no.4
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• pp.229-249
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• 2016

This study was conducted to create a digital archive for local cultural contents compiled from the records of westerners who stayed in Korea during the Enlightenment Period of Chosun. The compiled information were gathered from 22 records, and 10 main subjects, 40 sub-subjects and 239 mini-subjects were derived through the subject classification scheme. Item analysis was conducted through 38 metadata and input data types were classified and databased in Excel. Finally, a web-based digital archiving system was developed for searching and providing information through various access points. Suggestions for future research were made to expand archive contents through continuous excavation of westerners' records, to build an integrated information system of Korean digital archives incorporating individual archive systems, to develop standardization of classification schemes and a multidimensional classification system considering facet structure in cultural heritage areas, to keep consistency of contents through standardization of metadata format, and to build ontology using semantic search functions and data mining functions.

• The Journal of the Korea Contents Association
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• v.19 no.3
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• pp.275-287
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• 2019

As game players have been more diverse and new features of digital games have been emerged in recent days, it is important to find out and understand how recent game players recognize and classify digital games. Thirty game players conducted Q-analysis of twenty-nine Q-statements extracted from previous studies on game typology. By using a QUANL program, three different types were revealed. For game classification, 'Physical Environment Centric Players' type highly values external game elements from the outside perspectives. 'Contents Centric Players' type considers internal game elements as the most important criterion. 'Emotional Experience Centric Players' type values his/her subjective feeling and thoughts. Based on this study, it is expected to make a contribution in developing a framework of game players with their perspectives on game classification.

• Journal of the Korean Society for Library and Information Science
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• v.47 no.1
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• pp.221-247
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• 2013

The purpose of the study is to investigate and analyze the categories of online bookstores and to propose improvements. For the study, the category conformity was compared among eight Korean online bookstores selected; the book classification on the categories was compared from them. The results show that the category conformity was high among online bookstores, but the book classification on the categories was different on the bookstores. ISBN contents classification codes for books might not help to classify the books on the categories. Thus, the study proposes a new publication category for the book classification on categories of online bookstores.

• Journal of the Korean Institute of Intelligent Systems
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• v.1 no.3
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• pp.20-32
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• 1991

This study seeks a way a way of dealing with unformatted natural language considering fuzzy set theory. The goal of the study is to establish a framework of an effective language understanding system that is linked to language classification system This study has found that languate understanding is strongly influenced by the language classification. The understanding of language. This study shows that the precision of language classification depends upon the way of how the language is classified in advance. In this study, a fuzzy logic was used to improve the precision of language classification. It was considered that the fuzzy logic might be albe to distinctively classify nuatural language texts into pretinent homogenious groups where contents of the language were identical. Accordingly, in the study, it was expected that classification of language were precisely classified by the fuzzy logic. An experimentalsystems was designed to evaluate the performane of a natural language understanding system that was connected to a fuzzy language classification system. Finally, the experiment suggests that a successful language understanding should require an real time interaction between mem andmachine fuzzy provious language classification.

• Proceedings of the Korea Contents Association Conference
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• 2014.06a
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• pp.77-78
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• 2014

• Proceedings of the Korea Contents Association Conference
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• 2014.06a
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• pp.309-310
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• 2014

• Proceedings of the Korea Contents Association Conference
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• 2014.06a
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• pp.165-166
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• 2014

• Proceedings of the Korea Contents Association Conference
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• 2012.05a
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• pp.397-398
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• 2012

본 연구는 대학 홍보 전략에 활용하고 있는 마케팅PR 전략 활동을 연구 목적에 따라 3가지의 유목을 분류하고 각 유형에 맞는 사례를 조사하여 분석하고자 한다.

• Journal of the Korea Convergence Society
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• v.8 no.12
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• pp.39-47
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• 2017

The Internet have increased the number of digital web documents related to the history and traditions of Korean Culture. However, users who search for creators or materials related to traditional cultures are not able to get the information they want and the results are not enough. Document classification is required to access this effective information. In the past, document classification has been difficult to manually and manually classify documents, but it has recently been difficult to spend a lot of time and money. Therefore, this paper develops an automatic text classification model of traditional cultural contents based on the data of the Korean information culture field composed of systematic classifications of traditional cultural contents. This study applied TF-IDF model, Bag-of-Words model, and TF-IDF/Bag-of-Words combined model to extract word frequencies for 'Korea Traditional Culture' data. And we developed the automatic text classification model of traditional cultural contents using Support Vector Machine classification algorithm.