• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.95-110
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• 2013

Recently, the amount of unstructured data being generated through a variety of social media has been increasing rapidly, resulting in the increasing need to collect, store, search for, analyze, and visualize this data. This kind of data cannot be handled appropriately by using the traditional methodologies usually used for analyzing structured data because of its vast volume and unstructured nature. In this situation, many attempts are being made to analyze unstructured data such as text files and log files through various commercial or noncommercial analytical tools. Among the various contemporary issues dealt with in the literature of unstructured text data analysis, the concepts and techniques of opinion mining have been attracting much attention from pioneer researchers and business practitioners. Opinion mining or sentiment analysis refers to a series of processes that analyze participants' opinions, sentiments, evaluations, attitudes, and emotions about selected products, services, organizations, social issues, and so on. In other words, many attempts based on various opinion mining techniques are being made to resolve complicated issues that could not have otherwise been solved by existing traditional approaches. One of the most representative attempts using the opinion mining technique may be the recent research that proposed an intelligent model for predicting the direction of the stock index. This model works mainly on the basis of opinions extracted from an overwhelming number of economic news repots. News content published on various media is obviously a traditional example of unstructured text data. Every day, a large volume of new content is created, digitalized, and subsequently distributed to us via online or offline channels. Many studies have revealed that we make better decisions on political, economic, and social issues by analyzing news and other related information. In this sense, we expect to predict the fluctuation of stock markets partly by analyzing the relationship between economic news reports and the pattern of stock prices. So far, in the literature on opinion mining, most studies including ours have utilized a sentiment dictionary to elicit sentiment polarity or sentiment value from a large number of documents. A sentiment dictionary consists of pairs of selected words and their sentiment values. Sentiment classifiers refer to the dictionary to formulate the sentiment polarity of words, sentences in a document, and the whole document. However, most traditional approaches have common limitations in that they do not consider the flexibility of sentiment polarity, that is, the sentiment polarity or sentiment value of a word is fixed and cannot be changed in a traditional sentiment dictionary. In the real world, however, the sentiment polarity of a word can vary depending on the time, situation, and purpose of the analysis. It can also be contradictory in nature. The flexibility of sentiment polarity motivated us to conduct this study. In this paper, we have stated that sentiment polarity should be assigned, not merely on the basis of the inherent meaning of a word but on the basis of its ad hoc meaning within a particular context. To implement our idea, we presented an intelligent investment decision-support model based on opinion mining that performs the scrapping and parsing of massive volumes of economic news on the web, tags sentiment words, classifies sentiment polarity of the news, and finally predicts the direction of the next day's stock index. In addition, we applied a domain-specific sentiment dictionary instead of a general purpose one to classify each piece of news as either positive or negative. For the purpose of performance evaluation, we performed intensive experiments and investigated the prediction accuracy of our model. For the experiments to predict the direction of the stock index, we gathered and analyzed 1,072 articles about stock markets published by "M" and "E" media between July 2011 and September 2011.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.101-116
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• 2015

Recently, due to the development of smart devices and social media, vast amounts of information with the various forms were accumulated. Particularly, considerable research efforts are being directed towards analyzing unstructured big data to resolve various social problems. Accordingly, focus of data-driven decision-making is being moved from structured data analysis to unstructured one. Also, in the field of recommendation system, which is the typical area of data-driven decision-making, the need of using unstructured data has been steadily increased to improve system performance. Approaches to improve the performance of recommendation systems can be found in two aspects- improving algorithms and acquiring useful data with high quality. Traditionally, most efforts to improve the performance of recommendation system were made by the former approach, while the latter approach has not attracted much attention relatively. In this sense, efforts to utilize unstructured data from variable sources are very timely and necessary. Particularly, as the interests of users are directly connected with their needs, identifying the interests of the user through unstructured big data analysis can be a crew for improving performance of recommendation systems. In this sense, this study proposes the methodology of improving recommendation system by measuring interests of the user. Specially, this study proposes the method to quantify interests of the user by analyzing user's internet usage patterns, and to predict user's repurchase based upon the discovered preferences. There are two important modules in this study. The first module predicts repurchase probability of each category through analyzing users' purchase history. We include the first module to our research scope for comparing the accuracy of traditional purchase-based prediction model to our new model presented in the second module. This procedure extracts purchase history of users. The core part of our methodology is in the second module. This module extracts users' interests by analyzing news articles the users have read. The second module constructs a correspondence matrix between topics and news articles by performing topic modeling on real world news articles. And then, the module analyzes users' news access patterns and then constructs a correspondence matrix between articles and users. After that, by merging the results of the previous processes in the second module, we can obtain a correspondence matrix between users and topics. This matrix describes users' interests in a structured manner. Finally, by using the matrix, the second module builds a model for predicting repurchase probability of each category. In this paper, we also provide experimental results of our performance evaluation. The outline of data used our experiments is as follows. We acquired web transaction data of 5,000 panels from a company that is specialized to analyzing ranks of internet sites. At first we extracted 15,000 URLs of news articles published from July 2012 to June 2013 from the original data and we crawled main contents of the news articles. After that we selected 2,615 users who have read at least one of the extracted news articles. Among the 2,615 users, we discovered that the number of target users who purchase at least one items from our target shopping mall 'G' is 359. In the experiments, we analyzed purchase history and news access records of the 359 internet users. From the performance evaluation, we found that our prediction model using both users' interests and purchase history outperforms a prediction model using only users' purchase history from a view point of misclassification ratio. In detail, our model outperformed the traditional one in appliance, beauty, computer, culture, digital, fashion, and sports categories when artificial neural network based models were used. Similarly, our model outperformed the traditional one in beauty, computer, digital, fashion, food, and furniture categories when decision tree based models were used although the improvement is very small.

• The Journal of Korean Medicine
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• v.17 no.1 s.31
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• pp.280-301
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• 1996

This thesis is on the effects of the Injections of Mokhyangsunkisan extract, Mokhyangsunkisan plus Rheum undulatum L. extract and Palmisunkisan extract clinical experiments wre done with medicines to research their analgesic and anti-convulsive action and their efficiency on $O_3$ and Xylene-poisoned lung damage and the pulmonary thromboembolism of rats and mice. The results are as follows; 1. As to the analgesic action, each Injection of Mokhyangsunkisan extract, Mokhyangsunkisan plus Rheum undulatum L. extract and Palmisunkisan extract had significant effects. Among them the Injection of Mokhyangsunkisan plus Rheum undulatum L. extract had the highest effect. 2. As to the anti-convulsive action, each Injections of Mokhyangsunkisan extract and Palmisunkisan extract had significant effects whereas that of the Injection of Mokhvangsunkisan plus Rheum undulatum L. extract had no effect. 3. In the frsearch of the Lung TBA values of $O_3$-poisoned rats. each Injection of Mokhyangsunkisan extract and Palmisunkisan extract had significant effects whereas that of the Injection of Mokhyangsunkisan plus Rheum undulatum L. extract had no effect. 4. None of the Injection of Mokhyangsunkisan extract, Mokhyangsunkisan plus Rheum undulatum L, extract and Palmisunkisan extract had significant effects in the experiments about the variation of the $Na^+$ contents and $K^+$ contents in the serum electrolytes of the $O_3$-poisoned rats. 5. In the research of the Lung TBA values of Xylene-poisoned rats all the three Injections had prominent effects. 6. In the research of the Lung weight in Xylene-poisoned rats each Injections of Mokhyangsunkisan extract and Palmisunkisan extract had significant effects whereas that of the Injection of Mokhyangsunkisan plus Rheum undulatum L. extract had no effect. 7. In the experiments about the variation of the $Na^+$ contents in the serum electrolytes of the Xylene-poisoned rats the Injection of Mokhyangsunkisan extract had a significant effect whereas those of the Injections of Mokhyangsunkisan plus Rheum undulatum L. extract and Palmisunkisan extract had no significant effects. 8. None of the Injection of Mokhyangsunkisan extract, Mokhyangsunkisan plus Rheum undulatum L. extract and Palmisunkisan extract had significant effects in the experiments about the variation of the $K^+$ contents in the serum electrolytes of the Xylene-poisoned rats. 9. All the three Injections had prominent death-repressive effects on the pulmonary thromboembolism induced by Sodium Arachidonate. 10. Each Injection of Mokhyangsunkisan extract and Palmisunkisan extract had death-repressive effects on the pulmonary thromboembolism induced by ADP, whereas the Injection of Mokhyangsunkisan plus Rheum undulatum L. extract had a feeble death-repressive effect By all results of the clinical experiments. the following conclusions are drown; Each Injection of Mokhyangsunkisan extract and Palmisunkisan extract has analgesic and anti-convulsive effects and is also effective for the $O_3$ and Xylene-poisoned Lung damage and pulmonary thromboembolism of rats and mice. The Injection of Mokhyangsunkisan plus Rheum undulatum L. extract has on analgesic effect and is also effective for the pulmonary thromboembolism. Especially its analgesic effect is prominent. Therefore, each Injection of Mokhyangsunkisan extract and Palmisunkisan extract can be used for injection to improve the pulmonary functions whereas the Injection of Mokhyangsunkisan plus Rheum undulatum L. extract is partly effective for the improvement of the pulmonary function. In view of the results so far achieved, fluid acupuncture therapy can be applied as well as traditional way of oral administration of the decoction.

• Journal of Science Education
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• v.38 no.2
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• pp.302-316
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• 2014

The purpose of this study is to devise a Small-Scale Chemistry (SSC) lab program for primary school learners and to examine its effects on science learning achievement. In addition, it will be examined whether the type of learning groups affects the achievement or not. The participants in the current study were 173 6th graders from 6 classes of Y elementary school in Changwon city, Gyeongnam. Three classes(86) were assigned to the experimental group and the other three, the comparative group after checking the pre-homogeneity between the two groups through t-test on the scores of the science mid-term exam. We conducted five experimental sessions on the Acid and Base in the science textbook for the sixth graders. The students of one experimental class worked in pairs and another class worked individually, but the students of the comparative classes were divided into groups of six(one group with pair, another group with individual work in the SSC program, and the other group conducting the traditional experiment with groups of six students). The data were analyzed by t-test and ANOVA. The results showed that experimental learning using individual work in the SSC program compared to traditional experimental learning was effective in improving science learning achievement. also it was indicated that the teachers could reduce their burden of preparing for classes and of school hours when they utilized the SSC laboratory learning program. Teachers could also actively support students' experimental activities in employing the program. Based on the results, we suggest that the development of the SSC laboratory learning program is meaningful in the sense that this program can help elementary schoolers to improve science learning achievements more than the existing traditional experimental methods.

• The Journal of the Korea Contents Association
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• v.12 no.8
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• pp.114-122
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• 2012

The world focus on enhancing national prestige based on the value of traditional culture and history to preserve cultural heritage that make an effort to popularize in public. Hence, the true issue of paradigm for traditional culture are given at recreation for the value of cultural heritage. To study level of awareness of the importance in cultural heritage, proceed on experimental research for two groups that each group as for professionals and laymen. There are five experiment with two groups that of level of immersion, educational effect, interest, intelligibility score in the documentary in achieve which are recorded image and recorded film. The result of experiments, it showed difference between professionals and laymen, high scored of immersion and intelligibility score in professionals group of recorded image, other highly scored of immersion and educational effect in laymen of recorded film. Consequently, it will need historical recording documents to supply divisively with as considering levels and cognitive situation for professionals and laymen to satisfy their intention. And also, the needs for public to develop various source and contents of heritage to have people's interests. For the expert, it demand on educational projects and contents to be initiated in skills and arts.

• Korean Journal of Remote Sensing
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• v.28 no.4
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• pp.357-367
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• 2012

This paper presents a two-stage methodology for anomaly detection from hyperspectral imagery that consists of transform-based feature extraction and selection, and computation of a local spatial auto-correlation statistic. First, principal component transform and 3D wavelet transform are applied to reduce redundant spectral information from hyperspectral imagery. Then feature selection based on global skewness and the portion of highly skewed sub-areas is followed to find optimal features for anomaly detection. Finally, a local indicator of spatial association (LISA) statistic is computed to account for both spectral and spatial information unlike traditional anomaly detection methodology based only on spectral information. An experiment using airborne CASI imagery is carried out to illustrate the applicability of the proposed anomaly detection methodology. From the experiments, anomaly detection based on the LISA statistic linked with the selection of optimal features outperformed both the traditional RX detector which uses only spectral information, and the case using major principal components with large eigen-values. The combination of low- and high-frequency components by 3D wavelet transform showed the best detection capability, compared with the case using optimal features selected from principal components.

• The Journal of Society for e-Business Studies
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• v.8 no.3
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• pp.177-195
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• 2003

In a traditional customer support environment, mainly call centers or service centers are responsible for receiving inquiries from their customers via telephone calls. Due to the rapid growth of Internet with its widespread acceptance and accessibility, means of communication with customers in the traditional customer support center, such as telephones, letters, and direct-visiting, have been replaced by e-mails and bulletin board systems (BBSs) using the Internet constantly. BBSs are basically question and answer systems, they require some lead time to get answer from administrator. To reduce lead time, BBSs enable remote customers or users to log on and tap into a knowledge database that is generally formatted in the form of Frequently Asked Questions (FAQs) that provide answers and solutions to the common problems. And, many different types of the questions are mixed on the BBS. It is a burden to administrator. To build FAQs and to support BBS adminstrator, a supporting tool which is to categorize questions is helpful. In this research, we suggest an interactive question categorizing methodology which consists of steps to present question using keywords, identifying keywords' affinity, computing similarity among questions, and clustering questions. This methodology allows users to interact iteratively for clear manifestation of ambiguous questions. We also developed a prototype system, IQC (interactive question categorizer) and evaluated its performance using the comparison experiments with other systems. IQC is not a general purposed system, but it produces a good result in a given specific domain.

• Journal of The Korean Association For Science Education
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• v.17 no.1
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• pp.55-64
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• 1997

Experiments done in traditional physics laboratories have been criticized for giving too detailed instruction so that student could follow the experimental procedure without understanding. This type of experiment is often called "cookbook experiment." Cookbook experiment was known to be little help to understand the physics concepts and to increase student interest. To solve these problems with traditional cookbook experiment, non-directive introductory physics laboratory was designed and tried with the freshmen of Department of Physics Education of Seoul National University. Non-directive laboratory was characterized by the lack of step by step instruction for students to follow. The instruction students received consisted of the goal of experiment, a short introduction, and a list of suggested materials to be used. Student designed the experimental procedure and decided what material they wanted to use. One group submitted one lab report as a group to encourage cooperation among students. Lab report could be written in any form students wanted and no penalty point was given to poor data or inappropriate theory, etc to encourage taking risks. Penalty points were given if the students did not get involved during class hours. Student received extra point for being creative and / or working hard. Teaching assistants used Socratic dialogue in helping students to find their own way instead of explaining what they had to do. Students' interest about the non-directive experiment was studies at the of the semester. A questionnaire was made for students to answer. The questionnaire consisted of four categories, the equipment and the laboratory, the experimental procedure, the lab report, and teaching assistant. For each category, student were asked to explain the differences from other laboratory classes, features they liked and the reasons why they do, features they did not like and why they did not. At the end of the questionnaire, students were asked what hey wanted to change and what they did not. They also could put any opinion they had other than the questions asked. Student overall opinion was very positive. All the students said they liked the lack of detailed experimental procedure because it gave them the feeling of achievement, made them feel challenged and think in more diverse and creative ways. Students liked the lab report because group report forced them to discuss more and the free form lab report helped them to focus on the what they did. Student responses about the teaching assistant was also positive but not as enthusiastic as the experimental procedure or lab report. However students recognised that the role of the teaching assistant was as a guide, a supporter, or a facilitator.

• Journal of the Korean Society for Marine Environment & Energy
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• v.19 no.4
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• pp.341-348
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• 2016

Micro-algae, one of the biological resources for alternative energy, has been heavily studied. Among various methods to analyze the status of the micro-algae including counting, screening, and flocculation, the flocculation approach has been widely accepted in many critical applications such as red tide removal study or microalgae resource study. To characterize the flocculation status of the micro-alga. A traditional optical modality, i.e., photospectrometry, measuring the optical density of the flocs has been frequently employed. While this traditional optical method needs shorter time than the counting method in flocculation status analysis, it has relatively lower detection accuracy. To address this issue, a novel real-time micro-algae flocculation analysis method based on the lens-free shadow imaging technique (LSIT) is introduced. Both single cell detection and floc detection are simultaneously available with a proposed lens-free shadow image, confirmed by comparing the results with optical microscope images. And three shadow parameters, e.g., number of flocs, effective area of flocs, and maximum size of floc, enabling quantification of the flocculation phenomenon of micro-alga, are firstly demonstrated in this article. The efficacy of each shadow parameter is verified with the real-time flocculation monitoring experiments using custom developed cohesive agents.

• Journal of Korean Traditional Oncology
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• v.11 no.1
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• pp.75-93
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• 2006

Jiaweicitaowan (JWCTW) has been used to inhibit recurrence and metastasis of cancer in clinical practice. Further study has shown its anti-metastatic and anti-angiogenic effects. By applying in vitro and in vivo anti-angiogenic evaluation model, the author assayed the each ingredients of JWCTW. The author performed the following experiments and the results are listed as below: Cell viability assay showed that the viability was almost identical between that of the control and that of the ingredients extract 40 ${\mu}g/m{\ell}$ treated, except of hexane fraction of Curcumae Radix (40 ${\mu}g/m{\ell}$, 2.0% of control), ethylacetate fraction (40 ${\mu}g/m{\ell}$, 26.7%), butanol fraction (20 ${\mu}g/m{\ell}$, 87.2%; 40 ${\mu}g/m{\ell}$, 12.5%) of Cremastrae appendiculatae Tuber, water fraction of Persicae Semen (40 ${\mu}g/m{\ell}$, 82.7%), ethylacetate fraction of Hippocampus (40 ${\mu}g/m{\ell}$, 85.3%). The results of gelatin zymogram assay showed that the ingredients of JWCTW decreases the gelatinolytic activity of MMP-9 from ECV304, at the concentration of 10 ${\mu}g/m{\ell}$. In in vitro invasion assay, the ingredients of JWCTW effectively inhibited the invasion of cancer cells as compared with the control (+PMA) groups. In capillary-like tube formation assay, the hexane and ethylacetate fractions of Curcumae Radix, Cremastrae appendiculatae Tuber and Persicae Semen showed the dramatic inhibition effects on tube formation of ECV304 at the concentration of 40 ${\mu}g/m{\ell}$. In ex vivo rat aortic ring assay, the hexane and ethylacetate fractions of Curcumae Radix, Cremastrae appendiculatae Tuber and Persicae Semen showed the inhibition effects on angiogenesis of rat aorta at the concentration of 40 ${\mu}g/m{\ell}$. According to the above research, the anti-angiogenic effects of the ingredients of JWCTW was proved and it suggested that the more effective prescription for anti angiogenesis could be developed.