• The Journal of the Korea Contents Association
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• v.11 no.12
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• pp.466-474
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• 2011

Under the knowledge-based economy in 21C, the convergence and complexity in science and technology are being more active. Therefore, we have science and technology are classified properly, make not easy to construct the system to new next generation area. Thus we suggest the systematic solution method to flexibly extend classification scheme in order for content management and service organizations. In this way, we expect that the difficult of classification scheme management is minimized and the expense of it is spared.

• The Journal of Society for e-Business Studies
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• v.22 no.2
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• pp.61-77
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• 2017

Recently, the number of academic conference information on the Internet has rapidly increased, the automatic classification of academic conference information according to research subjects enables researchers to find the related academic conference efficiently. Information provided by most conference listing services is limited to title, date, location, and website URL. However, among these features, the only feature containing topical words is title, which causes information insufficiency problem. Therefore, we propose methods that aim to resolve information insufficiency problem by utilizing web contents. Specifically, the proposed methods the extract main contents from a HTML document collected by using a website URL. Based on the similarity between the title of a conference and its main contents, the topical keywords are selected to enforce the important keywords among the main contents. The experiment results conducted by using a real-world dataset showed that the use of additional information extracted from the conference websites is successful in improving the conference classification performances. We plan to further improve the accuracy of conference classification by considering the structure of websites.

• The Journal of the Korea Contents Association
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• v.17 no.9
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• pp.132-144
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• 2017

The fingerprint classification of categorizing fingerprints by classes should be used in order to improve the processing speed and accuracy in a fingerprint recognition system using a large database. The fingerprint classification methods extract features from the fingerprint ridges of a fingerprint and classify the fingerprint using learning and reasoning techniques based on the classes defined according to the flow and shape of the fingerprint ridges. In earlier days, many researches have been conducted using NIST database acquired by pressing or rolling finger against a paper. However, as automated systems using live-scan scanners for fingerprint recognition have become popular, researches using fingerprint images obtained by live-scan scanners, such as fingerprint data provided by FVC, are increasing. And these days the methods of fingerprint classification using Deep Learning have proposed. In this paper, we investigate the trends of fingerprint classification technology and compare the classification performance of the technology. We desire to assist fingerprint classification research with increasing large fingerprint database in improving the performance by mentioning the necessity of fingerprint classification research with consideration for fingerprint images based on live-scan scanners and analyzing fingerprint classification using deep learning.

• Journal of Korea Multimedia Society
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• v.10 no.3
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• pp.391-400
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• 2007

According to the recent advances in multimedia computing, storage and searching technology have made large volume of music contents become prevalent. Also there has been increasing needs for the study on efficient categorization and searching technique for music contents management. In this paper, a new classifying method using the local information of music content and music tone feature is proposed. While the conventional classifying algorithms are based on entire information of music content, the algorithm proposed in this paper focuses on only the specific local information, which can drastically reduce the computing time without losing classifying accuracy. In order to improve the classifying accuracy, it uses a new classification feature based on music tone. The proposed method has been implemented as a part of MuSE (Music Search/Classification Engine) which was installed on various systems including commercial PDAs and PCs.

• ETRI Journal
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• v.37 no.3
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• pp.541-550
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• 2015

In this paper, we propose a classification-based approach for hybridizing statistical machine translation and rulebased machine translation. Both the training dataset used in the learning of our proposed classifier and our feature extraction method affect the hybridization quality. To create one such training dataset, a previous approach used auto-evaluation metrics to determine from a set of component machine translation (MT) systems which gave the more accurate translation (by a comparative method). Once this had been determined, the most accurate translation was then labelled in such a way so as to indicate the MT system from which it came. In this previous approach, when the metric evaluation scores were low, there existed a high level of uncertainty as to which of the component MT systems was actually producing the better translation. To relax such uncertainty or error in classification, we propose an alternative approach to such labeling; that is, a cut-off method. In our experiments, using the aforementioned cut-off method in our proposed classifier, we managed to achieve a translation accuracy of 81.5% - a 5.0% improvement over existing methods.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.01a
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• pp.285-286
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• 2021

본 논문에서는 변환 학습을 기반으로 한 다중 클래스 이미지 장면 분류 방법을 제안하도록 한다. ImageNet 대형 이미지 데이터 세트에서 사전 훈련 된 네트워크 모델을 사용하여 다중 클래스의 자연 장면 이미지를 분류하였다. 실험에서 최적화 된 ResNet 모델은 Kaggle의 Intel Image Classification 데이터 세트에 분류되어 우수한 결과를 얻었다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.681-682
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• 2021

본 논문에서는 소규모 데이터 셋의 이미지 분류 작업에서 모델 과적 합 및 비 수렴을 해결하고 분류의 정확도를 높이는 데 주로 사용되는 few-shot 학습을 기반으로 한 새로운 이미지 분류 방법을 제안합니다.

• The Journal of the Korea Contents Association
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• v.17 no.9
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• pp.650-660
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• 2017

This study is to suggest a new method of analyzing personality types of characters in narrative. First, we examined the history of the taxonomy of character types that existed in narrative theories so far. Until now, the classification of character types in narrative theory consisted largely of a formal classification based on roles in narrative, a content classification based on human internal qualities, and a complementary classification in which the two classification criteria are united. The problem with the existing character classification type is difficult to categorize it in spite of the usefulness of the content classification based on human internal qualities. On the other hand, the classification based on the role of the character in the narrative does not help as much as a practical analysis methodology because the classification is formal. In this study, we try to solve this problem by introducing Shalom Schwartz's human value type, and to make human character's value type and human role correlated with each other as a new character analysis methodology. Schwartz's study of value type is a very effective method to grasp the motivation of human behavior, and it seems to be very meaningful in analyzing the directivity of characters.

• International Journal of Contents
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• v.14 no.1
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• pp.7-11
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• 2018

Digital technology has been changing everyday life of ordinary people let alone the structure of world industry. The elderly care service is also going through changes influenced by the unavoidable impact from torrents of digital technologies. There are numerous reports and news about the digital technologies increasing the efficiency and effectiveness of care service yet lacking systematic understanding of the sources of such improvement. This study aims to present a new classification framework for digital elderly care service innovation to fully utilize the power of digital technologies drawing on insights from innovation studies and service studies. First, 4 features of digital technologies are identified as sources of new value in service innovation. The co-creation of value by users and producers in service and technology development is discussed to illuminate users' contributions to service innovation. Communication of needs and ideas with producers and application of new technologies into everyday practice of life are identified as the source of new value which can be attributed to the elderly. Customization along with efficiency gains is the key to digital elderly care service innovation. The classification framework, thus, incorporates the needs of the elderly as one axis of criteria in the conventional technology-centered framework. The new classification framework would help give due weight to user-driven or demand-driven innovation in the elderly care service R&D activities.

• The Journal of the Korea Contents Association
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• v.2 no.1
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• pp.68-76
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• 2002

Clustering is representative method of components classification. But, previous clustering method that use cohesion and coupling can not be effective, because design pattern has consisted by relation between classes. In this paper, we classified design patterns with special quality of pattern structure. Classification by clustering had expressed higher correctness degree than classification by facet. Therefore, can do that it is effective that classify design patterns using clustering algorithms that is automatic classification method. When we are searching design patterns, classification of design patterns can compare and analyze similar patterns because similar patterns is saved to same category. Also we can manage repository efficiently because of using and storing link information of patterns.