• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.219-240
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• 2023

Conversational AI which allows users to interact with satisfaction is a long-standing research topic. To develop conversational AI, it is necessary to build training data that reflects real conversations between people, but current Korean datasets are not in question-answer format or use honorifics, making it difficult for users to feel closeness. In this paper, we propose a conversation dataset (KOMUChat) consisting of 30,767 question-answer sentence pairs collected from online communities. The question-answer pairs were collected from post titles and first comments of love and relationship counsel boards used by men and women. In addition, we removed abuse records through automatic and manual cleansing to build high quality dataset. To verify the validity of KOMUChat, we compared and analyzed the result of generative language model learning KOMUChat and benchmark dataset. The results showed that our dataset outperformed the benchmark dataset in terms of answer appropriateness, user satisfaction, and fulfillment of conversational AI goals. The dataset is the largest open-source single turn text data presented so far and it has the significance of building a more friendly Korean dataset by reflecting the text styles of the online community.

• Asia Marketing Journal
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• v.16 no.1
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• pp.21-33
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• 2014

When the negative event is published, the company tends to go through the negative impact on the firm performance. Especially, with the SNS, the negative event is instantly spread on indefinite region so the impact seems bigger than the period before the SNS media appearance. It seems that everyone considers the SNS media impact on the firm performance quite big. However, there has been no empirical study on the impact comparison on the firm performance between pre and post SNS media occurrence periods. This study tries to empirically compare the impact of the negative event on the firm performance between pre and post SNS media appearance. Our study starts fromthe basic but not verified question; Does really the negative event have more negative impact in the post-SNS-occurrence period than in the pre-SNS-occurrence period? In order to examine the impact of the negative publicity on firm performance in two eras, pre and post SNS media appearance, we used CAR (Cumulative Abnormal Resturns) model. By using this model, we could verify the statistical significance of cumulative abnormal returns in market between before and after the events. For event samples, we focused on food manufacturers and collected the negative events from 1991 to 2003 for pre-SNS occurrence period, and from 2010 to 2013 for post-SNS occurrence period. Based on the listed food companies at KOSPI, we researched Naver News Library (newslibrary.naver.com) and Naver News (news.naver.com) for all the individual negative events published for both periods. Firm returns data were collected from TS 2000 (KOCO Info) and market portfolio data were collected from KRX Exchange. Through our empirical analysis, our finding is interesting to note that the type of events differently influences on the firm performance. With the SNS, the health-related events have influence on the firm performance 'after the event day' whereas the company behavior trust events have influence 'before the event day'. Our findings have implications for management. When a negative event directly related to or threatening customers or their life such as health, it is crucial to fix up the situation right after the event occurs. On the other hand, when a negative event is not publicly available information such as company behavior trust, it is important for marketers to strengthen the firms' trust reputation and control the bad WOM before the event.

• The Journal of Korean Obstetrics and Gynecology
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• v.36 no.4
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• pp.96-120
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• 2023

Objectives: This study reports the findings that support the efficacy of herbal medicine (HM) for premenstrual syndrome (PMS). Methods: We conducted meta-analysis of findings from randomized controlled trials (RCTs) for PMS treated with HM. The articles were published before July 2022, located using 9 databases (Pubmed, EMBASE, Cochrane Library, CINAHL, CNKI, CiNii, SCIENCE ON, KoreaMed, OASIS). Results: We observed 2,034 studies, of which 23 RCTs met our inclusion criteria. The risk of bias in the included studies was relatively unclear or high. Meta-analysis of 3 RCTs showed that HM group had a significantly higher total effective rate than the western medicine group (RR 1.20 [95% CI 1.06, 1.36, p=0.004]). Meta-analysis of 1 RCT showed that HM group had a significantly lower symptom score (MD -3.04 [95% CI -5.36, -0.72, p=0.01]), while there was no significant difference in daily record of severity of problems scale (MD -20.52 [95% CI -49.33, 8.29, p=0.16]). Conclusions: HM significantly improved PMS symptoms than general treatment and no serious adverse events were reported. However, the evidence on the effectiveness and safety of HM for PMS was not enough to provide reliable results due to the small number and low quality of included studies. We believe that rigorous RCTs will lead to more reliable evidence of the intervention.

• Journal of the Korean Society for information Management
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• v.41 no.1
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• pp.367-387
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• 2024

This study aims to identify the recent trends and intellectual structure of international research in the field of catalog, which is undergoing a major change due to the enactment of new standards and rules and the anticipated future. For this purpose, we collected 680 articles published in the 14 years since 2010 and analyzed 1,942 author keywords extracted from them after preprocessing. The main findings of the analysis are as follows First, overseas cataloging research has seen notable growth since 2017. Second, the most frequent research topics were: cataloging, metadata, RDA, university libraries, authority control, linked data, FRBR, catalog, LCSH, libraries, andonline cataloging. Third, the research themes were divided into two clusters, one related to the traditional aspects of library cataloging and the other related to the more recently discussed topics of authority control, cooperative cataloging, RDA, and linked data, which were further subdivided into 14 subclusters. Fourth, we looked at the growth index and standard performance index of the 14 keyword clusters and found that all but one cluster showed growth in terms of discipline growth. This study is significant in that it can be used as a basis for predicting the future development of inventories for Korean academia and the field and for related education.

• Therapeutic Science for Rehabilitation
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• v.13 no.2
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• pp.27-40
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• 2024

Objective : This study aimed to conduct a systematic review of the assessment tools used to assess the housing environment of older adults. Methods : Data were collected from January 2015 to August 31st, 2023, by searching databases including the Cochrane Library, PubMed, and ProQuest. From the 267 articles, nine assessment tools were selected for analysis based on their original instruments. These tools were categorized and systematically organized for analysis based on their frequency of use, assessment purposes, sub-domains, scales, and other relevant criteria. Results : Among the nine tools, HOME FAST and IPAQ-E were the most frequently used (20% each). The objectives of these tools are to assess friendliness, physical barriers, fall prevention, dementia-friendly environments, physical activity, and accessibility. The measurement scope encompassed various factors, such as outdoor spaces, buildings, transportation, housing, and community support. Conclusion : When considering the suitability of housing for the older adults population, providing foundational data for the rational selection of evaluation tools with logical validity is important. This includes factors such as the objectives and measurement scopes of housing environment assessment tools.

• Journal of Physiology & Pathology in Korean Medicine
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• v.26 no.4
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• pp.551-556
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• 2012

The database for the oriental medicine had been existed in documentation in past times and it has been developed to the database type for random accesses in the information society. However, the aspects of the database are not so diversified and the database for the bio herbal material exists in widened type dictionary style. It is a situation that the database which handles the in-depth raw herbal medicines is not sufficient in its quantity and quality. Korean wild grape is a deciduous plant categorized into the Vitaceae and it was found experimentally that it has various medical effects. It is one of the medical materials with higher potentiality of academic study and commercialization recently because it has a bigger possibility to be applied into diverse industrial fields including the medical product for health, food and beauty. We constituted the cooperative system among the Muju cluster business group for Korean mountain wild grapes, Physiology Laboratory in Kyung Hee University Oriental Medicine and Medical Classics Laboratory in Kyung Hee University Oriental Medicine with a view to focusing on such potentiality and a database for Korean wild grapes was made a touchstone for establishing the in-depth database for the single bio medical materials. First of all, the literatures based on the North East Asia in ancient times had been categorized into the classical literature (Korean literature published by government organization, Korean classical literature, Chinese classical literature and classical literature fro Korean and Chinese oriental medicine) and modern literature (Modern literature for oriental medicine, modern literature for domestic and foreign herbal medicine) to cover the eastern and western research records and writings related to Korean wild grapes and the text-mining work has been performed through the cooperation system with the Medical Classics Laboratory in Kyung Hee University Oriental Medicine. First of all, the data for the experiment and theory for Korean wild grape were collected for the Medline database controlled by the Parliament Library of USA to arrange the domestic and foreign theses with topic for Korean wild grapes and the network hyperlink function and down load function were mounted for self-thesis searching function and active view based on the collected data. The thesis searching function provides various auxiliary functions and the searching is available according to the diverse searching/queries such as the name of sub species of Korean wild grape, the logical intersection index for the active ingredients, efficacy and elements. It was constituted for the researchers who design the Korean wild grape study to design of easier experiment. In addition, the data related to the patents for Korean wild grape which were collected from European Patent Office in response to the commercialization possibility and the system available for searching and view was established in the same viewpoint. Perl was used for the query programming and MS-SQL for database establishment and management in the designing of this database. Currently, the data is available for free use and the address is as follows. http://163.180.41.43:8011/index.html

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.179-200
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• 2019

Word-of-mouth (WoM) is defined by consumer activities that share information concerning consumption. WoM activities have long been recognized as important in corporate marketing processes and have received much attention, especially in the marketing field. Recently, according to the development of the Internet, the way in which people exchange information in online news and online communities has been expanded, and WoM is diversified in terms of word of mouth, score, rating, and liking. Social media makes online users easy access to information and online WoM is considered a key source of information. Although various studies on WoM have been preceded by this phenomenon, there is no meta-analysis study that comprehensively analyzes them. This study proposed a method to extract major researches by applying text mining techniques and to grasp the main issues of researches in order to find the trend of WoM research using scholarly big data. To this end, a total of 4389 documents were collected by the keyword 'Word-of-mouth' from 1941 to 2018 in Scopus (www.scopus.com), a citation database, and the data were refined through preprocessing such as English morphological analysis, stopwords removal, and noun extraction. To carry out this study, we adopted main path analysis (MPA) and word co-occurrence network analysis. MPA detects key researches and is used to track the development trajectory of academic field, and presents the research trend from a macro perspective. For this, we constructed a citation network based on the collected data. The node means a document and the link means a citation relation in citation network. We then detected the key-route main path by applying SPC (Search Path Count) weights. As a result, the main path composed of 30 documents extracted from a citation network. The main path was able to confirm the change of the academic area which was developing along with the change of the times reflecting the industrial change such as various industrial groups. The results of MPA revealed that WoM research was distinguished by five periods: (1) establishment of aspects and critical elements of WoM, (2) relationship analysis between WoM variables, (3) beginning of researches of online WoM, (4) relationship analysis between WoM and purchase, and (5) broadening of topics. It was found that changes within the industry was reflected in the results such as online development and social media. Very recent studies showed that the topics and approaches related WoM were being diversified to circumstantial changes. However, the results showed that even though WoM was used in diverse fields, the main stream of the researches of WoM from the start to the end, was related to marketing and figuring out the influential factors that proliferate WoM. By applying word co-occurrence network analysis, the research trend is presented from a microscopic point of view. Word co-occurrence network was constructed to analyze the relationship between keywords and social network analysis (SNA) was utilized. We divided the data into three periods to investigate the periodic changes and trends in discussion of WoM. SNA showed that Period 1 (1941~2008) consisted of clusters regarding relationship, source, and consumers. Period 2 (2009~2013) contained clusters of satisfaction, community, social networks, review, and internet. Clusters of period 3 (2014~2018) involved satisfaction, medium, review, and interview. The periodic changes of clusters showed transition from offline to online WoM. Media of WoM have become an important factor in spreading the words. This study conducted a quantitative meta-analysis based on scholarly big data regarding WoM. The main contribution of this study is that it provides a micro perspective on the research trend of WoM as well as the macro perspective. The limitation of this study is that the citation network constructed in this study is a network based on the direct citation relation of the collected documents for MPA.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.71-89
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• 2016

Sentiment analysis is used for identifying emotions or sentiments embedded in the user generated data such as customer reviews from blogs, social network services, and so on. Various research fields such as computer science and business management can take advantage of this feature to analyze customer-generated opinions. In previous studies, the star rating of a review is regarded as the same as sentiment embedded in the text. However, it does not always correspond to the sentiment polarity. Due to this supposition, previous studies have some limitations in their accuracy. To solve this issue, the present study uses a supervised sentiment classification model to measure a more accurate sentiment polarity. This study aims to propose an advanced sentiment classifier and to discover the correlation between movie reviews and box-office success. The advanced sentiment classifier is based on two supervised machine learning techniques, the Support Vector Machines (SVM) and Feedforward Neural Network (FNN). The sentiment scores of the movie reviews are measured by the sentiment classifier and are analyzed by statistical correlations between movie reviews and box-office success. Movie reviews are collected along with a star-rate. The dataset used in this study consists of 1,258,538 reviews from 175 films gathered from Naver Movie website (movie.naver.com). The results show that the proposed sentiment classifier outperforms Naive Bayes (NB) classifier as its accuracy is about 6% higher than NB. Furthermore, the results indicate that there are positive correlations between the star-rate and the number of audiences, which can be regarded as the box-office success of a movie. The study also shows that there is the mild, positive correlation between the sentiment scores estimated by the classifier and the number of audiences. To verify the applicability of the sentiment scores, an independent sample t-test was conducted. For this, the movies were divided into two groups using the average of sentiment scores. The two groups are significantly different in terms of the star-rated scores.

• Environmental Analysis Health and Toxicology
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• v.15 no.4
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• pp.131-137
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• 2000

The release of hazardous waste materials into the environment poses serious risks in humans and ecosystems. The risk assessment of environmental pollutants including hazardous chemicals requires a comprehensive measurement of hazard and exposure of the chemicals that can be achieved by toxicity evaluation using a biological system such as biomarkers. In this report we have tried to develop a biomarker used to elucidate a molecular basis of, and to monitor abnormal behaviors caused by diazinon in Japanese medaka (Oryzias latipes) as a model organism. First, an attempt was made to clone tyrosine hydroxylase gene from Japanese medaka that would be a candidate for a biomarker for neuronal modulations and behaviors. For monitoring experiments at behavioral and molecular biological levels, the fish were treated under different sublethal conditions of diazinon and their behavioral responses were observed . In this study we have successfully cloned a partial TH gene from the medaka fish through PCR screening of an ovary cDNA library. DNA sequencing analysis revealed that the amplified fragment was 327 bp encoding 109 amino acids. Comparing the DNA sequence of medaka TH with other species, TH gene revealed the DNA sequence was completely identical to that of rat TH. In the RT-PCR, 330 Up of mRNA was consistently amplified in all the treated samples including control There were no significant differences in the TH expression level regardless of treating concentrations (1∼5,000 ppb) and time (0∼48 hr) The reason appeared to be that RT-PCR was not performed using through a quantitative analysis normalized against an actin gene expression. Organ or tissue - specific detection of TH activity and mRNA as biomarkers will be a useful monitoring tool for neurobehavioral changes in fish influenced by toxic chemicals. Furthermore, quantitative analysis of locomotive patterns and its correlation with the neurochemical and molecular data would be highly useful in measuring toxicity and hazard ofvarious environmental pollutants.

• Journal of Life Science
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• v.20 no.3
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• pp.411-415
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• 2010

Anisakis simplex is one of the parasitic nematodes, and has a complex life cycle in crustaceans, fish, squid or whale. When people eat under-processed or raw fish, it causes anisakidosis and also plays a critical role in inducing serious allergic reactions in humans. However, no web-based database on A. simplex at the level of DNA or protein has been so far reported. In this context, we constructed a web-based database for Anisakis research. To build up the web-based database for Anisakis research, we proceeded with the following measures: First, sequences of order Ascaridida were downloaded and translated into the multifasta format which was stored as database for stand-alone BLAST. Second, all of the nucleotide and EST sequences were clustered and assembled. And EST sequences were translated into amino acid sequences for Nuclear Localization Signal prediction. In addition, we added the vector, E. coli, and repeat sequences into the database to confirm a potential contamination. The web-based database gave us several advantages. Only data that agrees with the nucleotide sequences directly related with the order Ascaridida can be found and retrieved when searching BLAST. It is also very convenient to confirm contamination when making the cDNA or genomic library from Anisakis. Furthermore, BLAST results on the Anisakis sequence information can be quickly accessed. Taken together, the Web-based database on A. simplex will be valuable in developing species specific PCR markers and in studying SNP in A. simplex-related researches in the future.