• Journal of the Korean Society for Library and Information Science
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• v.42 no.2
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• pp.371-392
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• 2008

The books and circulation-related data in the Online Public Access Catalog System of the H-Public library were collected and analyzed in this paper. The methods which may be applied to the Customer Relationship Management in a public library based on the results were also suggested here. Collected data were 57,927 bibliographic data of books, 11,871 patron data and 27,145 circulation records. The type of collections. circulation frequencies, total number of circulated books, publication year, and use factor as relation factor from the analyzed data of circulation records were extracted. They were also analyzed, and verified by various statistical methods such as correlation coefficient, non-parametric method, etc.

• The Journal of the Korea Contents Association
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• v.14 no.11
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• pp.592-601
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• 2014

This study examines newspaper obituaries in Korean media and English media. Initially, 100 Korean obituaries were collected from the JoongAng Ilbo which span over more than three years, from May 2011 to August 2014. After that, another 50 Korean obituaries were gathered from the DongA Ilbo which were published over the same time period with the JoongAng Ilbo. As for English newspapers, obituaries from the New York Times and the Guardian were included in the corpus for comparison. First, the structure and composition of obituaries in each language (Korean and English) are compared. Korean obituaries show a pattern of a combination of a death notice and an obituary. Second, distinct features of each newspaper are discussed. The JoongAng Ilbo has its obituary section titled "Life and Memories", and the DongA Ilbo's obituaries are under the heading of "Rest in Peace." Obituaries in the New York Times appear in print on different pages of the paper according to the deceased's field of interest. Following discussion of formal structure and characteristics of each newspaper, Korean and English obituaries will be compared in terms of content and cultural context.

• The Journal of the Korea Contents Association
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• v.17 no.11
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• pp.389-397
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• 2017

Recently semantic web document is produced and added in repository in a cloud computing environment and requires an intelligent semantic agent for analytical classification of documents and information retrieval. The traditional methods of information retrieval uses keyword for query and delivers a document list returned by the search. Users carry a heavy workload for examination of contents because a former method of the information retrieval don't provide a lot of semantic similarity information. To solve these problems, we suggest a key word frequency and concept matching based semantic clustering model using hadoop and NoSQL to improve classification accuracy of the similarity. Implementation of our suggested technique in a cloud computing environment offers the ability to classify and discover similar document with improved accuracy of the classification. This suggested model is expected to be use in the semantic web retrieval system construction that can make it more flexible in retrieving proper document.

• Journal of Korean Library and Information Science Society
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• v.46 no.1
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• pp.321-344
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• 2015

This paper presents a fusion approach to sentiment detection that combines multiple sources of evidence to retrieve blogs that contain opinions on a specific topic. Our approach to finding opinionated blogs on topic consists of first applying traditional information retrieval methods to retrieve blogs on a given topic and then boosting the ranks of opinionated blogs based on the opinion scores computed by multiple sentiment detection methods. Our sentiment detection strategy, whose central idea is to rely on a variety of complementary evidences rather than trying to optimize the utilization of a single source of evidence, includes High Frequency module, which identifies opinions based on the frequency of opinion terms (i.e., terms that occur frequently in opinionated documents), Low Frequency module, which makes use of uncommon/rare terms (e.g., "sooo good") that express strong sentiments, IU Module, which leverages n-grams with IU (I and you) anchor terms (e.g., I believe, You will love), Wilson's lexicon module, which uses a collection-independent opinion lexicon constructed from Wilson's subjectivity terms, and Opinion Acronym module, which utilizes a small set of opinion acronyms (e.g., imho). The results of our study show that combining multiple sources of opinion evidence is an effective method for improving opinion detection performance.

• The Journal of the Acoustical Society of Korea
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• v.30 no.5
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• pp.295-302
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• 2011

The purpose of this study was to develop Korean Consonant Perception Test (KCPT), that is a phonemic level including elementary data to evaluate speech and consonant perception ability of the normal and the hearing impaired qualitatively and quantitatively. KCPT was completed with meaningful monosyllabic words out of possible all Korean monosyllabic words, considering articulation characteristics, the degree of difficulty, and the frequency of the phonemic appearance, after assembling a tentative initial and final consonants testing items using four multiple-choice method which were applied to the seven final consonant regulation and controlled with the familiarity of the target words. Conclusively, the final three hundred items were developed including two- and one-hundred items for initial and final testing items, respectively, with the evaluation of the 20 normal hearing adults. Through this process, the final KCPT was composed upon the colloquial frequency following identification of no speakers' variances statistically and elimination of the highly difficult items. The 30 hearing impaired were tested with KCPT and found that the half lists, A and B, were not different statistically and the initial and final testing items were appropriate for evaluating initial and final consonants, respectively.

• Journal of Food Hygiene and Safety
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• v.34 no.3
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• pp.251-262
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• 2019

In this study, we analyzed Korean dietary habits with food intake data from the Korea National Health and Nutrition Examination Survey (KNHANES) and the Korea Centers for Disease Control and Prevention and we proposed a set of management guidelines for future Korean dietary habits. A total of 839 food items (1,419 foods) were analyzed according to the food catagories in "Food Code", which is the representative food classification system in Korea. The average total daily food intake was 1,585.77 g/day, with raw and processed foods accounting for 858.96 g/day and 726.81 g/day, respectively. Cereal grains contributed to the highest proportion of the food intake. Over 90% of subjects consumed cereal grains (99.09%) and root and tuber vegetables (95.80%) among the top 15 consumed food groups. According to the analysis by item, rice, Korean cabbage kimchi, apple, radish, egg, chili pepper, onion, wheat, soybean curds, potato, cucumber and pork were major (at least 1% of the average daily intake, 158.6 g/day) and frequently (eaten by more than 25% of subjects, 5,168 persons) consumed food items, and Korean spices were at the top of this list. In the case of kimchi, the proportion of intake of Korean cabbage kimchi (64.89 g/day) was the highest. In the case of alcoholic beverages, intake was highest by order of beer (63.53 g/day), soju (39.11 g/day) and makgeolli (19.70 g/day), and intake frequency was high in order of soju (11.3%), beer (7.2%), and sake (6.6%). Analysis results by seasonal intake trends showed that cereal grains have steadily decreased and beverages have slightly risen. In the case of alcoholic beverage consumption frequency, some kinds of makgeolli, wine, sake, and black raspberry wine have decreased gradually year by year. The consumption trend for kimchi has been gradually decreasing as well.

• Journal of KIISE
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• v.44 no.6
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• pp.621-627
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• 2017

Collaborative filtering is a technique that effectively recommends unrated items for users. Collaborative filtering is based on the similarity of the items evaluated by users. The existing top-N recommendation methods are based on pair-wise and list-wise preference models. However, these methods do not effectively represent the relative preference of items that are evaluated by users, and can not reflect the importance of each item. In this paper, we propose a new method to represent user's latent preference by combining an existing preference model and the notion of inverse user frequency. The proposed method improves the accuracy of existing methods by up to two times.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06b
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• pp.315-317
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• 2012

지식iN 등의 지식검색 서비스는 잘못된 답변으로 인한 낮은 신뢰성과 다수의 중복 답변 등의 문제점을 가진다. 질의문 '세상에서 가장 큰 나라'에 대해서 관련된 모든 질문과 답변을 제시하지 않고 질의문과 관련된 다수의 답변을 분석하여 답변 '러시아'를 추천하여 제시할 수 있다면 지식검색의 효용성과 신뢰성이 크게 향상될 수 있다. 본 논문에서는 질문-답변의 유형을 단어, 글, 도표, 목록의 네가지로 분류하고, 그 중 단어 유형에 대한 답변 추천 방법을 제시한다. 질의문에 대해 검색된 질문을 군집화하고, 질문에 대한 답변들에 대해서 TF, IDF, 어휘간 거리 정보를 다양하게 결합하여 어휘의 점수를 계산한다. 각 군집에서 가장 높은 점수를 가지는 어휘를 해당 군집에서 가장 중요한 어휘로 보고 추천 정답으로 제시한다. 단어 유형인 질문 100개에 대한 네이버 지식iN에 대한 시스템 평가에서 추천된 상위 1위에 대해서는 68%의 정답률을, 상위 5위까지에 대해서는 89%의 정답률을 보였다.

• Journal of the Korean Society for Library and Information Science
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• v.41 no.4
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• pp.295-314
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• 2007

IFLA's FRBR model is a significant contribution to cataloging on both theoretical and practical grounds. This paper provides a brief overview of FRBR, a methodology for applying the FRBR work concept to a random sample of 1,000 bibliographic records taken from Korean National Bibliographic, and estimates of the number of works in Korean National Bibliographic and their associated characteristics, based on analysis of the sample. FRBR model can be applied to 16.9% of all works in Korean National Bibliographic. Results suggest that the majority of benefits associated with applying FRBR to Korean National Bibliographic could be obtained by concentrated on a relatively small number of complex works.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.22 no.3
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• pp.247-267
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• 2011

The purpose of this study is to investigate knowledge structure of knowledge organization research area in Korea. The study employed content analysis and network analysis to analyze degree centrality, betweenness, and eigenvector as well as frequency of words. It also analyzes research articles published during the period of 2000-2001. The study can be summarized that the network of keywords of knowledge organization researches is compact and complicated. Cataloging and classification play important roles in the network, and metadata and ontology becomes focal areas in knowledge organization. On the other hand, networks of authorships and authors are broad and fragmented. Collaboration is not active enough.