• The Korean Society of Law and Medicine
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• v.20 no.1
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• pp.83-107
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• 2019

In order to resolve a dispute over a medical accident, the court is in the process of appraising the medical records for medical professionals to report their medical expertise or judgments using that knowledge. The consequences of expert opinion about a medical accident are only one of the methods of evidence as a reference. Therefore, in principle, the court should not be bound to the results, but the court, which is not a medical expert, can not completely rule out medical expert opinion as to whether there is medical malpractice and causality. Therefore, it can not be denied that the proportion of expert opinion of medical records in the dispute about medical accidents is high and it has an important influence on the judgement of the court. In this paper, we examine the significance and function of expert opinion of the medical accident, examine the appraising procedure of the medical records in the court and the appraising procedure of the medical accidents of the Korean medical dispute mediation arbitrator do. In addition, I would like to examine what kind of attitude is being taken in response to expert opinion of medical records in Korea to court, to examine the implications of the case of Japan as a foreign system, and to suggest improvement points in the expert opinion procedure of medical record filing in Korea. In particular, I would like to suggest improvements on issues such as the fairness of the expert opinion of medical records and the delays in litigation due to delays in the process of expert opinion.

• KIISE Transactions on Computing Practices
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• v.22 no.7
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• pp.338-343
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• 2016

Today, opinion reviews on the Web are often used as a means of information exchange. As the importance of opinion reviews continues to grow, the number of issues for opinion spam also increases. Even though many research studies on detecting spam reviews have been conducted, some limitations of gold-standard datasets hinder research. Therefore, we introduce a new dataset called "Paraphrased Opinion Spam (POS)" that contains a new type of review spam that imitates truthful reviews. We have noticed that spammers refer to existing truthful reviews to fabricate spam reviews. To create such a seemingly truthful review spam dataset, we asked task participants to paraphrase truthful reviews to create a new deceptive review. The experiment results show that classifying our POS dataset is more difficult than classifying the existing spam datasets since the reviews in our dataset more linguistically look like truthful reviews. Also, training volume has been found to be an important factor for classification model performance.

• The Journal of the Korea Contents Association
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• v.18 no.10
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• pp.121-133
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• 2018

This study begins with focus on the public opinion and political views on embracing Yemeni refugees in Jeju. The public opinion is demanding amendment or even abolition of the Refugee Act. The argument opposing Yemeni refugees is persuasive enough in terms of public order and safety, cultural conflicts and economic interests, but it is going against the universal and authentic values that must be pursued by a forward-looking society. It is natural that the power exerting political discretion keeps an eye on public opinion. However, no matter how many people express it, unjustified public opinion must not be a foundation for political decision. This study will examine the shadows of public opinion and related concepts for those reasons, and review Augustine's concept of 'love' as a value to refer to in making a communal decision. Conflicts lead to insecurity and rift. Without sensus communis (common sense), the rift will not be healed. This study raises the need to resolve such conflicting state and seeks insight from Augustine.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.5
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• pp.243-253
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• 2012

An opinion mining technique which was developed from document classification in area of data mining now becomes a common interest in domestic as well as international industries. The core of opinion mining is to decide precisely whether an opinion document is a positive or negative one. Although many related approaches have been previously proposed, a classification accuracy was not satisfiable enough to applying them in practical applications. A opinion documents written in Korean are not easy to determine a polarity automatically because they often include various and ungrammatical words in expressing subjective opinions. Proposed in this paper is a new approach of classification of opinion documents, which considers only a frequency of word patterns and excludes the grammatical factors as much as possible. In proposed method, we express a document into a bag of words and then apply a learning algorithm using a frequency of word patterns, and finally decide the polarity of the document using a score function. Additionally, we also present the experiment results for evaluating the accuracy of the proposed method.

• Journal of Advanced Marine Engineering and Technology
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• v.34 no.6
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• pp.871-879
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• 2010

In this paper, we present a system that classifies comments on a news article into a user opinion called a polarity (positive or negative). The system is a kind of document classification system for comments and is based on machine learning techniques like support vector machine. Unlike normal documents, comments have their body that can influence classifying their opinions as polarities. In this paper, we propose a feature weighting scheme using such characteristics of comments and several resources for opinion classification. Through our experiments, the weighting scheme have turned out to be useful for opinion classification in comments on Korean news articles. Also Korean character n-grams (bigram or trigram) have been revealed to be helpful for opinion classification in comments including lots of Internet words or typos. In the future, we will apply this scheme to opinion analysis of comments of product reviews as well as news articles.

• Journal of Korean Society for Quality Management
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• v.47 no.1
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• pp.97-108
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• 2019

Purpose: The purpose of this study is to propose a new Risk Priority Number(RPN) evaluation method which analyzes value of product functions by mining customer opinions in Social Network Service(SNS). Methods: A traditional RPN is measured by three evaluation standards (Severity, Occurrence, Detection) which are analyzed by manufacturing engineers and researchers. On the other hand, these standards are analyzed by customers' viewpoints through SNS opinion mining in this research. In order to extract customer feedbacks from textual data sets, the methodology in this paper implies natural language processing, hereby collecting product related data sets and analyzing the opinions automatically. An emotional polarity of an opinion indicates severity, while the number of negative opinion shows occurrence, and the entire number of customer opinion refers to detection. Results: The results of this study are as follows; As a result of the CRPN evaluation, it is confirmed that the features evaluated as risky are highly likely to be improved in the next series. Therefore, CRPN is an effective risk assessment model that reflects customer feedback. Conclusion: Reflecting customer feedback is a useful tool for risk assessment of the product as well as for developing new products and improving existing products.

• Asian Journal for Public Opinion Research
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• v.2 no.1
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• pp.1-2
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• 2014

• Asian Journal for Public Opinion Research
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• v.1 no.3
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• pp.151-152
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• 2014

• Asian Journal for Public Opinion Research
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• v.1 no.2
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• pp.71-72
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• 2014

• Asian Journal for Public Opinion Research
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• v.1 no.4
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• pp.232-233
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• 2014