• The Journal of the Korea Contents Association
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• v.17 no.1
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• pp.692-700
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• 2017

Based on the sexual offenses committed in school, the present study investigated differences between habitual/repeated sexual offenses and one-off sexual offenses in terms of offender characteristics, victim characteristics, and offense characteristics. We examined a total of 218 sexual offense cases committed in school. As a result, we found significant differences in the age, job, and residential area between habitual/repeated and one-off sexual offenders in school. In addition, notable differences were found between habitual/repeated and one-off sexual offense cases in the age and alcohol use of the victim. Moreover, habitual/repeated and one-off sexual offenses in school differed significantly by offense planning, method of approaching the victim, type of sexual behavior, and victim resistance. Furthermore, we conducted regression analyses and identified multiple factors that contributed to lasting of the sexual offense in school. Finally, we discussed limitations of the present study and made suggestions for future research.

• The Journal of the Korea Contents Association
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• v.17 no.8
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• pp.610-618
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• 2017

Sex offense by medical practitioners has been occurring continuously in Korea leading to not only patients but the general public expressing anxiety and increased distrust in the medical field. The government has been pushing ahead with the legislation or revision of law to increase the penalties on sexual offenders in response to requests for a stricter legal framework to address sex offense cases and has expressed a strong commitment to actively resorting to administrative corrective measures towards sexually offending medical practitioners. Unlike such an overall social atmosphere, the Judiciary that is in charge of applying the law seems not to perceive the seriousness of sex offense cases committed by medical practitioners. A doctor who had sexually assaulted a middle school female student during medical treatment at a pediatric hospital was found innocent by the supreme court, which was a ruling in direct contrast to overall public sentiment. As such, this study seeks to analyze the precedent on cases involving sex offense by medical practitioners with a focus on the above-mentioned case and present implications. The study seeks to dispel distrust in the overall medical field by addressing the gap in legal interpretation towards sex offense committed by medical practitioners and thus provide basic data that can help the general public receive quality medical services in a safer environment.

• Journal of Information Technology Services
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• v.15 no.3
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• pp.71-95
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• 2016

In recent years, text mining has been used to extract meaningful insights from the large volume of unstructured text data sets of various domains. As one of the most representative text mining applications, topic modeling has been widely used to extract main topics in the form of a set of keywords extracted from a large collection of documents. In general, topic modeling is performed according to the weighted frequency of words in a document corpus. However, general topic modeling cannot discover the relation between documents if the documents share only a few terms, although the documents are in fact strongly related from a particular perspective. For instance, a document about "sexual offense" and another document about "silver industry for aged persons" might not be classified into the same topic because they may not share many key terms. However, these two documents can be strongly related from the R&D perspective because some technologies, such as "RF Tag," "CCTV," and "Heart Rate Sensor," are core components of both "sexual offense" and "silver industry." Thus, in this study, we attempted to discover the differences between the results of general topic modeling and R&D perspective topic modeling. Furthermore, we package social issues from the R&D perspective and present a prototype system, which provides a package of news articles for each R&D issue. Finally, we analyze the quality of R&D perspective topic modeling and provide the results of inter- and intra-topic analysis.