• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.25-38
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• 2019

Selecting high-quality information that meets the interests and needs of users among the overflowing contents is becoming more important as the generation continues. In the flood of information, efforts to reflect the intention of the user in the search result better are being tried, rather than recognizing the information request as a simple string. Also, large IT companies such as Google and Microsoft focus on developing knowledge-based technologies including search engines which provide users with satisfaction and convenience. Especially, the finance is one of the fields expected to have the usefulness and potential of text data analysis because it's constantly generating new information, and the earlier the information is, the more valuable it is. Automatic knowledge extraction can be effective in areas where information flow is vast, such as financial sector, and new information continues to emerge. However, there are several practical difficulties faced by automatic knowledge extraction. First, there are difficulties in making corpus from different fields with same algorithm, and it is difficult to extract good quality triple. Second, it becomes more difficult to produce labeled text data by people if the extent and scope of knowledge increases and patterns are constantly updated. Third, performance evaluation is difficult due to the characteristics of unsupervised learning. Finally, problem definition for automatic knowledge extraction is not easy because of ambiguous conceptual characteristics of knowledge. So, in order to overcome limits described above and improve the semantic performance of stock-related information searching, this study attempts to extract the knowledge entity by using neural tensor network and evaluate the performance of them. Different from other references, the purpose of this study is to extract knowledge entity which is related to individual stock items. Various but relatively simple data processing methods are applied in the presented model to solve the problems of previous researches and to enhance the effectiveness of the model. From these processes, this study has the following three significances. First, A practical and simple automatic knowledge extraction method that can be applied. Second, the possibility of performance evaluation is presented through simple problem definition. Finally, the expressiveness of the knowledge increased by generating input data on a sentence basis without complex morphological analysis. The results of the empirical analysis and objective performance evaluation method are also presented. The empirical study to confirm the usefulness of the presented model, experts' reports about individual 30 stocks which are top 30 items based on frequency of publication from May 30, 2017 to May 21, 2018 are used. the total number of reports are 5,600, and 3,074 reports, which accounts about 55% of the total, is designated as a training set, and other 45% of reports are designated as a testing set. Before constructing the model, all reports of a training set are classified by stocks, and their entities are extracted using named entity recognition tool which is the KKMA. for each stocks, top 100 entities based on appearance frequency are selected, and become vectorized using one-hot encoding. After that, by using neural tensor network, the same number of score functions as stocks are trained. Thus, if a new entity from a testing set appears, we can try to calculate the score by putting it into every single score function, and the stock of the function with the highest score is predicted as the related item with the entity. To evaluate presented models, we confirm prediction power and determining whether the score functions are well constructed by calculating hit ratio for all reports of testing set. As a result of the empirical study, the presented model shows 69.3% hit accuracy for testing set which consists of 2,526 reports. this hit ratio is meaningfully high despite of some constraints for conducting research. Looking at the prediction performance of the model for each stocks, only 3 stocks, which are LG ELECTRONICS, KiaMtr, and Mando, show extremely low performance than average. this result maybe due to the interference effect with other similar items and generation of new knowledge. In this paper, we propose a methodology to find out key entities or their combinations which are necessary to search related information in accordance with the user's investment intention. Graph data is generated by using only the named entity recognition tool and applied to the neural tensor network without learning corpus or word vectors for the field. From the empirical test, we confirm the effectiveness of the presented model as described above. However, there also exist some limits and things to complement. Representatively, the phenomenon that the model performance is especially bad for only some stocks shows the need for further researches. Finally, through the empirical study, we confirmed that the learning method presented in this study can be used for the purpose of matching the new text information semantically with the related stocks.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.1-23
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• 2013

To discover significant social issues such as unemployment, economy crisis, social welfare etc. that are urgent issues to be solved in a modern society, in the existing approach, researchers usually collect opinions from professional experts and scholars through either online or offline surveys. However, such a method does not seem to be effective from time to time. As usual, due to the problem of expense, a large number of survey replies are seldom gathered. In some cases, it is also hard to find out professional persons dealing with specific social issues. Thus, the sample set is often small and may have some bias. Furthermore, regarding a social issue, several experts may make totally different conclusions because each expert has his subjective point of view and different background. In this case, it is considerably hard to figure out what current social issues are and which social issues are really important. To surmount the shortcomings of the current approach, in this paper, we develop a prototype system that semi-automatically detects social issue keywords representing social issues and problems from about 1.3 million news articles issued by about 10 major domestic presses in Korea from June 2009 until July 2012. Our proposed system consists of (1) collecting and extracting texts from the collected news articles, (2) identifying only news articles related to social issues, (3) analyzing the lexical items of Korean sentences, (4) finding a set of topics regarding social keywords over time based on probabilistic topic modeling, (5) matching relevant paragraphs to a given topic, and (6) visualizing social keywords for easy understanding. In particular, we propose a novel matching algorithm relying on generative models. The goal of our proposed matching algorithm is to best match paragraphs to each topic. Technically, using a topic model such as Latent Dirichlet Allocation (LDA), we can obtain a set of topics, each of which has relevant terms and their probability values. In our problem, given a set of text documents (e.g., news articles), LDA shows a set of topic clusters, and then each topic cluster is labeled by human annotators, where each topic label stands for a social keyword. For example, suppose there is a topic (e.g., Topic1 = {(unemployment, 0.4), (layoff, 0.3), (business, 0.3)}) and then a human annotator labels "Unemployment Problem" on Topic1. In this example, it is non-trivial to understand what happened to the unemployment problem in our society. In other words, taking a look at only social keywords, we have no idea of the detailed events occurring in our society. To tackle this matter, we develop the matching algorithm that computes the probability value of a paragraph given a topic, relying on (i) topic terms and (ii) their probability values. For instance, given a set of text documents, we segment each text document to paragraphs. In the meantime, using LDA, we can extract a set of topics from the text documents. Based on our matching process, each paragraph is assigned to a topic, indicating that the paragraph best matches the topic. Finally, each topic has several best matched paragraphs. Furthermore, assuming there are a topic (e.g., Unemployment Problem) and the best matched paragraph (e.g., Up to 300 workers lost their jobs in XXX company at Seoul). In this case, we can grasp the detailed information of the social keyword such as "300 workers", "unemployment", "XXX company", and "Seoul". In addition, our system visualizes social keywords over time. Therefore, through our matching process and keyword visualization, most researchers will be able to detect social issues easily and quickly. Through this prototype system, we have detected various social issues appearing in our society and also showed effectiveness of our proposed methods according to our experimental results. Note that you can also use our proof-of-concept system in http://dslab.snu.ac.kr/demo.html.

• Journal of Technologic Dentistry
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• v.17 no.1
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• pp.41-57
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• 1995

This study was conducted to collect and analyze previous information in order to manage efficience, improve experience effect and promote employment rate. The questionnaire interview with 27 chief of dental Laboratory refered clinical experience in technology department about clinical experience in 14 Jumior colleges were also investigated. The results were summarried as follows : The portion of age of 35-39 among chief of dental Laboratory was 40.7% which was the highest, that of male was 96.3%, that of junior college graduate was 97.5%, that of 10years experience was 92.6% and that of ceramic technician was 85.2%, 63.0% dental laboratory for clinical experience was a bore space of 30pyong. Aspect of dental laboratory management, manufacturing all part of prosthetic restoration was 29.6%, othodontic appliance and ceramic restoration was 7.4%, 3.8%, each. The percentage of 40.7 was having connection with 30-3a dental clinics and referring case per day was 10-19 cases(40.7%), manufacturing time of referred prosthetic restoration was 3-4 days(77.8%), places preparing seminar room for education was 29.6%, above a place of 40pyong was 11.1% 30-34 pyong and 35-39 pyong was 7.4% each. During training of 2 years education course student, 18.5% was rack of thorough occupational career. While 44.4% will want the more salary among 3years education course student, 74.1% will expect the more dental techmicians would engaged in their field, 51.9% will hope improve of their theory and practice, 29.6% be expected better skill and 14.8% be expected better theory. Attitude of clinical experience places was distributed by 59.3% of offering only experience chance, 25.9% of wasting time and 29.0% of annoying. The big emphasis of climical experience was thorough occupational career(44.4%). The clinical experience places of our college were selected after direct visiting, so their condition of management was not that bad but most of dental laboratory were poor in management state and working environment. Therefore it is difficult to choose appropriate places and dental Laboratory are also limited manpower and time as suppliers. So that it recommended to induce flexible management of experience period by interval and rotation of experience places among college and to applicate intern-system for employment ant industry-college cooperation aspect.

• Journal of Bio-Environment Control
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• v.26 no.4
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• pp.378-385
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• 2017

In this study, we evaluated the changes of fruit quality indices during fruit development and ripening in Korean new pear cultivar 'Changjo', developed from a cross between 'Tama' and '81-1-27' ('Danbae' ${\times}$ 'Okusankichi') in 1995 and named in 2009, to determine appropriate harvest time and to enhance the market quality and broaden the cultivation area. The fruits of 'Changjo' pears harvested from 132 days after full bloom (DAFB) to 160 DAFB. Fruit growth and quality indices were monitored at 1 week interval by measuring fruit weight, length, diameter, firmness, and taste related quality indices. The calculated fruit fresh weight increased continuously with fruit development and reached to an average of 594g on Sep. 20 (160 DAFB). The ratio of length to diameter declines as fruit maturation progress, resulting in 0.898 for ripe fruit stage as a round oblate shape. Flesh firmness of 'Changjo' pears showed over 30N until 153 DAFB and then decreased abruptly with fruit ripening, reaching a final level of about 26.44N on 160 DAFB. Starch content of fruit sap was also decreased abruptly after 146 DAFB which decreased almost half of the fruits harvested at 139 DAFB. In parallel with the decrease of flesh firmness, ethanol insoluble solids (EIS) content decreased sharply with fruit ripens, only 50% of EIS was detected on the fruits harvested on 160 DAFB when compared to that of the fruits harvested on 139 DAFB (Aug. 30). The maximum value of soluble solids contents was observed in the fruits harvested on 153 DAFB, resulting in $14.2^{\circ}Brix$. The changes of skin color difference $a^*$ which means loss of green color occurred only after 139 DAFB, coincide with the decrease of SPAD value of the fruit skin. The sugars of the 80% ethanol soluble fraction consisted mainly of fructose, sorbitol, glucose and sucrose, also increased during maturation and ripening. Fructose and sucrose contents were larger than those of glucose and sorbitol in flesh tissues. These results were explained that stored starch is converted to soluble sugars during fruit maturation, mainly in fructose and sucrose increasing the sweetness of this cultivar. Total polyphenols were increased up to middle of fruit maturation (146 DAFB) and then decreased continuously until the end of fruit maturation. Consequently, our results suggested that the commercial harvest time of 'Changjo' pears should not be passed 153 DAFB and late harvest of this cultivar would not good for quality maintenance during shelf-life. As a result of the post-harvest low-temperature acclimation experiment during the short-term transportation period, fruits harvested at 146 DAFB tended to maintain higher firmness after 14 days of simulated marketing at $25^{\circ}C$ compared to fruits harvested at 153 DAFB regardless of temperature set. And, the slower the rate of decrease to the final transport temperature of $5^{\circ}C$, the higher the incidence of internal browning and ethylene production. Therefore, in order to suppress the physiological disorder and to maintain the fruit quality when exporting to Southeast Asia in the 'Chanjo' pears, it is desirable to lower the temperature of the fruits within a short time after harvest and to set the harvest time before 146 days after full bloom.

• (The) Research of the performance art and culture
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• no.43
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• pp.47-78
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• 2021

This study was written to examine the acceptance of pansori in movies based on pansori, and to explore changes in modern society's perception and expectations of pansori. A pansori is getting the love of the upper and lower castes in the late Joseon period, but loses the status at the time of the Japanese colonial rule and Korean War. In response, the country designated pansori as an important intangible cultural asset in 1964 to protect the disappearance of pansori. Until the 1980s, however, pansori did not gain popularity by itself. After the 2000s, Pansori tried to breathe in with the contemporary public due to the socio-cultural demand to globalize our culture. And now Pansori is one of the most popular cultures in the world today, as the pop band Feel the Rhythm of KOREA shows. The changing public perception of pansori and its status in modern society can also be seen in the mass media called movies. This study explored the process of this change with six films based on pansori, from "Seopyeonje" directed by Lim Kwon-taek in 1993 to the film "The Singer" in 2020. First, the films "Seopyeonje" and "Hwimori" were produced in the 1990s. Both of these films show the reality of pansori, which has fallen out of public interest due to the crisis of transmission in the early and mid-20th century. And in the midst of that, he captured the scene of a singer struggling fiercely for the artistic completion of Pansori itself. Next, look at the film "Lineage of the Voice" in 2008 and "DURESORI: The Voice of East" in 2012. These two films depict the growth of children who perform art, featuring contemporary children who play pansori and Korean traditional music. Pansori in these films is no longer an old piece of music, nor is it a sublime art that is completed in harsh training. It is only naturally treated as one of the contemporary arts. Finally, "The Sound of a Flower" in 2015 and "The Singer" in 2020. The two films constructed a story from Pansori's history based on the time background of the film during the late Joseon Dynasty, when Pansori was loved the most by the people. This reflects the atmosphere of the times when traditions are used as the subject of cultural content, and shows the changed public perception of pansori and the status of pansori.

• Advances in pediatric surgery
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• v.8 no.2
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• pp.143-155
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• 2002

A survey on biliary atresia was made among 26 members of the Korean Association of Pediatric Surgeons. The members were required to complete a questionnaire and a case registration form for each patient during the twentyone-year period of 1980-2000. Three hundred and eighty patients were registered from 18 institutions. The average number of patients per surgeon was one to two every year. The male to female ratio was 1:1.3. The age of patients on diagnosis with biliary atresia was on average $65.4{\pm} 36.2$ days old. The national distribution was 32.8% in Seoul, 25.3% in Gyoungki-Do, 21.6% in Gyoungsang-Do, 9.27% in Choongchung-Do, etc. in order. The most common clinical presentation was jaundice (98.4%) and change of stool color (86.2%) was second. Two hundred eighty (74.7%) of 375 patients were operated by 80 days of age. Three hundred thirty six (9 1.9%) of 366 patients were operated on by the original Kasai procedure, and 305 (84.3%) of 362 patients were observed by bile-drainage postoperatively. The overall postoperative complication rate was 18.5% and the overall postoperative mortality rate was 6.8%. The associated anomalies were observed in 72 cases (22.5%). One hundred ninty five (64.7%) of 302 patients have been alive in follow-up and 49 (25.1%) have survived over 5 years without problem after operation. Ascending cholangitis, varices and ascites affected survival significantly, and the important long-term prognostic factor was the occurrence of complications.