• Journal of the Korean Data and Information Science Society
• /
• v.16 no.4
• /
• pp.781-790
• /
• 2005

Nowaday, statistical data with coherence, accuracy and timeliness are necessary to government, company and research center for decision making or research. In other words, the importance of statistical data quality is steadily increasing. Thus, in this paper, we suggest necessity of measuring customer satisfaction with NSO products for enhancing quality. And we construct measurement scale for measuring customer satisfaction based on the statistical quality indicators. Also we advise use of structural equation model in relation analysis for statistic quality elevation.

• Journal of the Korean Data and Information Science Society
• /
• v.15 no.4
• /
• pp.845-853
• /
• 2004

This study is to adjust the focus on the statistical survey about the rates of application for the 2005 Susi second semester admission to Universities in Daegu, Kyungbook. The decrease of population for university admission and the change of paradigm of selecting a field of specialization in university will have an adverse effect on ratios of admission. This is very important to the future of university in Daegu, Kyungbook.

• Communications for Statistical Applications and Methods
• /
• v.9 no.1
• /
• pp.281-289
• /
• 2002

In this paper, we considered an application of the bootstrap method for logit model. Estimation of type I error probability, the bootstrap p-values and bootstrap confidence intervals of parameter were proposed. Small sample Monte Carlo simulation were conducted in order to compare proposed method with existing normal theory based asymptotic method.

• Communications for Statistical Applications and Methods
• /
• v.7 no.3
• /
• pp.927-935
• /
• 2000

In this paper we propose a poll system n the internet. This system expects to increase the confidence of the internet poll results by sampling theory(proportional allocation). This system provides a cross-tale and result of hypothesis test which plays an important role for decision making. These results do offer a few statistical packages(such as SAS, SPSS) in the world wide web.

• Journal of the Korean Data and Information Science Society
• /
• v.20 no.4
• /
• pp.615-627
• /
• 2009

In micro marketing promotion, it is important to know the behavior of customers. In this study we are interested in the forecasting of repurchase of customers from customers' behavior. By analyzing the cosmetic transaction data we derive some variables which play an important role in the knowledge of the customers' behavior and in the modeling of repurchase. As modeling tools we use the decision tree, logistic regression and neural network model. Finally we decide to use the decision tree as a final model since it yields the smallest RASE (root average squared error) and the greatest correct classification rate.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.11 no.1
• /
• pp.73-84
• /
• 1986

A statistical method is proposed which estimates an edge that is one of the basic features in image understanding. The conventional edge detection techniques are performed well for a deterministic singnal, but are not satisfactory for a statistical signal. In this paper, we use the likelihood function which takes account of the statistical property of a signal, and derive the decision function from it. We propose the maximum likelihood edge detection technique which estimates an edge point which maximizes the decision function mentioned above. We apply this technique to statistecal signals which are generated by using the random number generator. Simnulations show that the statistical edge detection technique gives satisfactory results. This technique is extended to the two-dimensional image and edges are found with a good accuracy.

• Journal of Korean Society for Quality Management
• /
• v.44 no.1
• /
• pp.1-16
• /
• 2016

Purpose: This paper reviews the papers on statistical quality control issues which are published in Journal of the Korean Society for Quality Management (KSQM) since 1965. The literature review is purposed to survey a variety of statistical quality control issues. Methods: By grouping all of statistical quality control issues into 3 categories:; quality inspections, control charts, and process capability analysis. Results: Grouping all of papers on statistical quality control published in journal of the KSQM for 50 years into 3 categories, we provide a chronological roadmap for individual categories, and summarize the contents and contributions of surveyed papers. Conclusion: The review paper is expected to provide future direction to improve statistical quality control theories and applications in manufacturing and service industries.

• International Journal of Quality Innovation
• /
• v.5 no.1
• /
• pp.52-67
• /
• 2004

Successful implementation of statistical process control techniques requires for operational definitions and precise measurements. Nevertheless, very often analysts can dispose of process data available only by linguistic terms, that would be a waste to neglect just because of their intrinsic vagueness. Thus a hybrid approach, which integrates fuzzy set theory and common statistical tools, sounds useful in order to improve effectiveness of statistical process control in such a case. In this work, a fuzzy approach is adopted to manage linguistic information, and the use of a Chi-squared control chart is proposed to monitor process performance.

• Communications for Statistical Applications and Methods
• /
• v.8 no.2
• /
• pp.515-530
• /
• 2001

Recently Korean statistician have more chance to work with other researcher in other countries at international level. Especially the 53rd Scientist meeting of he International Statistical Institute(ISI) will be held in Seoul, Rep. of Korea at Aug 22-29, 2001. The fields of Statistics in Korea have been affected a lot from American Statistical Society. In this research communication, I would like to introduce a short history of he Italian statistical society and their major research topic and outputs. The contents will help us to understand the Italian statistician, and it can be a conner-stone to the future relationship between Korean statistician and Italian statistician.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.10
• /
• pp.3230-3255
• /
• 2022

Causality mining in NLP is a significant area of interest, which benefits in many daily life applications, including decision making, business risk management, question answering, future event prediction, scenario generation, and information retrieval. Mining those causalities was a challenging and open problem for the prior non-statistical and statistical techniques using web sources that required hand-crafted linguistics patterns for feature engineering, which were subject to domain knowledge and required much human effort. Those studies overlooked implicit, ambiguous, and heterogeneous causality and focused on explicit causality mining. In contrast to statistical and non-statistical approaches, we present Bidirectional Encoder Representations from Transformers (BERT) integrated with Multi-level Feature Networks (MFN) for causality recognition, called BERT+MFN for causality recognition in noisy and informal web datasets without human-designed features. In our model, MFN consists of a three-column knowledge-oriented network (TC-KN), bi-LSTM, and Relation Network (RN) that mine causality information at the segment level. BERT captures semantic features at the word level. We perform experiments on Alternative Lexicalization (AltLexes) datasets. The experimental outcomes show that our model outperforms baseline causality and text mining techniques.