• Journal of the Korean Association of Geographic Information Studies
• /
• v.9 no.1
• /
• pp.149-157
• /
• 2006

The purpose of this study is to search for location potential in Busan metropolitan city and to support decision-making in land use policy. As basis work for the analysis of the location potential, we build rank-map database by using the 11 index. And then by using rank-map, we carried out the location potential ($P_i$) analysis. As a result, we found that many commercial use located in Rank 1 to 2. Also, Rank 4-7 must be made an un-commercial use in assignment of land use zone. These data can be effectively used for land use plan in Busan metropolitan city as the basis data.

• Korean Journal of Animal Reproduction
• /
• v.21 no.2
• /
• pp.191-195
• /
• 1997

The objective of this study were to compare two methods of analysis of milk urea nitrogen (MUN) and to relate conentration of MUN to pregnancy rate in dairy cows. The Azotest and Sigma method for MUN analysis were compared. The Azotest consistently underestimated the Sigma values for same samples, except for those in rank 3. The CV for the Azotest, within each rank, were less than 15%, demonstrating acceptable repeatability of the Azotest within a rank. Concentrations of MUN higher or lower than MUN in rank 3 and 4 were associated with decreased pregnancy rate. Mun concentrations in rank 5 and 6 were associated with a, pp.oximately a 16 percentage point decrease in pregnancy rate. Mun concentrations in rank 5 and 6 were associated with a, pp.oximately a 16 percentage point decrease in pregnancy rate after AI in dairy cow. This results suggest that Azotest may be benificial to dairy producers to monitor urea nitrogen concentration in their herd in efforts to maintain or improve reproductive efficiency.

• Journal of Korea Port Economic Association
• /
• v.25 no.2
• /
• pp.95-114
• /
• 2009

The aim of this paper is to evaluate weight and priority values for 'inner consisted factors' and 'outer requested factors' of logistics system using the AHP(Analytic Hierarchicy Process) method. As for analysis regarding inner consisted factors, the results were shown as follows: a road transportation (0.312) as first rank; a marine transportation (0.269) as second rank; a railway transportation (0.239) as third rank; an air transportation (0.118) as fourth rank, and a pipeline transportation (0.063) as fifth rank. In terms of analysis regarding outer requested factors, the results were came out as follows: an infrastructure (0.322) as first rank; a performance (0.206) as second rank; an information system (0.151) as third rank; a human resources (0.121) as fourth rank, a business environment (0.075) as fifth rank; a connectivity (0.073) as sixth rank, and a political environment (0.052) as seventh rank.

• Journal of Digital Contents Society
• /
• v.19 no.1
• /
• pp.157-163
• /
• 2018

People who use SNS publish their diverse ideas on SNS every day. The data posted on the SNS contains many people's thoughts and opinions. In particular, popular keywords served on Twitter compile the number of frequently appearing words in user posts and rank them. However, this method is sensitive to unnecessary data simply by listing duplicate words. The proposed method determines the ranking based on the topic of the word using the relationship diagram between words, so that the influence of unnecessary data is less and the main word can be stably extracted. For the performance comparison in terms of the descending keyword rank and the ratios of meaningless keywords among high rank 20 keywords, we make a comparison between the proposed scheme which is based on morphological analysis and PageRank, and the existing scheme which is based on the number of appearances. As a result, the proposed scheme and the existing scheme have included 55% and 70% of meaningless keywords among high rank 20 keywords, respectively, where the proposed scheme is improved about 15% compared with the existing scheme.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2010.07a
• /
• pp.75-78
• /
• 2010

웹 검색에는 기존의 정보검색(Information Retrieval) 시스템에서와 다르게 문서 간 하이퍼링크 정보를 바탕으로 각 웹 문서의 고유 중요도를 추정하는 방식이 자주 이용된다. 링크 분석에 기반한 알고리즘 중 PageRank 알고리즘은 구글의 웹 검색 서비스에 적용된 것으로 알려져 있다. 이런 PageRank 알고리즘에 따라 중요도를 계산하는 경우 색인된 웹 문서수가 증가함에 따라 계산에 필요한 CPU 자원의 사용도 함께 증가하며, 문서 수가 수 억 페이지에 달하면 하나의 서버에서는 계산을 수행할 수 없다는 문제가 있다. 본 논문에서는 이런 문제점을 해소하기 위해 여러 대의 서버를 PageRank 계산 용 클러스터로 사용할 수 있는 방법을 제시한다. 제시된 방법은 고속의 LAN을 이용하여 여러 대의 서버를 연결하고 반복적인 행렬 계산을 병렬로 수행할 수 있어 계산 시간을 단축시킬 수 있다. 이런 서버 클러스터 구현을 위해 멀티 쓰레딩 프로그램이 작성되었으며, PageRank 계산에 사용되는 행렬 데이터를 적은 양의 메모리만으로 표현 가능하도록 하였다.

• The Journal of the Korea Contents Association
• /
• v.17 no.1
• /
• pp.201-212
• /
• 2017

This study presented the new evaluation index which can evaluate the discrimination of DEA models. To evaluate the discrimination of DEA models, data were analyzed using importance index as suggested in previous study and the coefficient of variation as suggested in this study for the discrimination evaluation. This study selected the CCR-DEA, BCC-DEA, entropy, bootstrap, super efficiency, and cross efficiency DEA model for the discrimination evaluation and accomplished empirical analysis. In order to grasp the rank correlation of the models, this study implemented the rank correlation analysis between the efficiency of CCR model and BCC model and entropy, bootstrap, super efficiency, and efficiency of the cross efficiency model. The obtained results of this study are as follows. First, the discrimination rank of models using the importance index and the coefficient of variation was shown to be identical. Therefore, the coefficient of variation can be used the discrimination evaluation index of DEA model. Second, the discrimination of the super efficiency model was found to be the highest rank among 4 models according to the analysis of this present study. Third, the highest rank correlation with CCR model was the super efficiency model. In addition, the super efficiency model was found to be the highest rank correlation with BCC model.

• Asia pacific journal of information systems
• /
• v.25 no.3
• /
• pp.548-562
• /
• 2015

The growing popularity of mobile application has led to researchers and practitioners needing to understand users' mobile application download behaviors. Using large-scale transaction data obtained from a leading Korean telecommunications company, we empirically explore how application download rank, which appears to users when they decide to download a new application, affects their extended mobile application download. This terminology refers to downloading an additional application in the same category as those that they have already downloaded. We also consider IT characteristics, user characteristics, and application type that might be associated with the extended application download. The analysis generates the following result. Overall, a higher rank of a new application encourages the extended application download, but the linear relationship between the rank and the extended application download disappears when critical rank points are incorporated into the model. Further, no quadratic effect of rank is found in the extended application download. Based on the results, we suggest theoretical and managerial implications.

• Korean Journal of Mathematics
• /
• v.28 no.1
• /
• pp.123-136
• /
• 2020

In this paper, we give an explicit formula as a rational function for the Ihara zeta function of every finite connected graph without degree one vertices whose circuit rank is two.

• Journal of Korea Multimedia Society
• /
• v.21 no.1
• /
• pp.45-50
• /
• 2018

This research paper describes how to summarize music lyrics using the TextRank algorithm. This method can summarize music lyrics as important lyrics. Therefore, we recommend music more effectively than analyzing the number of words and recommending music.

• Journal of Korean Institute of Industrial Engineers
• /
• v.40 no.1
• /
• pp.18-33
• /
• 2014

A Word is the smallest unit for text analysis, and the premise behind most text-mining algorithms is that the words in given documents can be perfectly recognized. However, the newly coined words, spelling and spacing errors, and domain adaptation problems make it difficult to recognize words correctly. To make matters worse, obtaining a sufficient amount of training data that can be used in any situation is not only unrealistic but also inefficient. Therefore, an automatical word extraction method which does not require a training process is desperately needed. WordRank, the most widely used unsupervised word extraction algorithm for Chinese and Japanese, shows a poor word extraction performance in Korean due to different language structures. In this paper, we first discuss why WordRank has a poor performance in Korean, and propose a customized WordRank algorithm for Korean, named KR-WordRank, by considering its linguistic characteristics and by improving the robustness to noise in text documents. Experiment results show that the performance of KR-WordRank is significantly better than that of the original WordRank in Korean. In addition, it is found that not only can our proposed algorithm extract proper words but also identify candidate keywords for an effective document summarization.