• Tuberculosis and Respiratory Diseases
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• v.48 no.2
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• pp.166-179
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• 2000

Background: The main reason for the failure of anti-cancer chemotherapy is the build up of resistance by cancer cells to apoptosis. The activation of NF-${\kappa}B$ in many cancer cell lines is reported to be underlying mechanism behind the build up of resistance of cancer cells to apoptosis. However, this relationship varied depending on the cells used in the experiments. In this study, the role of NF-${\kappa}B$ activation in the TNF-$\alpha$-induced apoptosis in lung cancer cell line was evaluated. Methods: NCI-H157 cells were used in all experiments. Cells were exposed to a high dose of TNF-$\alpha$(20 ng/ml) for 24 or 48 hours with or without blocking NF-${\kappa}B$ activation. TNF-$\alpha$-induced activation of NF-${\kappa}B$ was inhibited either by overexpression of $I{\kappa}B{\alpha}$-super repressor($I{\kappa}B{\alpha}$-SR) or by pre-treatment with proteasome inhibitor. Cell viability and apoptosis were evaluated with MTT assay and Western blot analysis for PARP fragment, respectively. Results: Cell viability of NCI-H157 cells was not affected by TNF-$\alpha$ treatment alone; however, combined treatment with TNF-$\alpha$ and cycloheximide reduced cell viability significantly, indicating that resistance to TNF-$\alpha$ is mediated by the new proteins synthesized after TNF-$\alpha$ stimulation. To evaluate the role of NF-${\kappa}B$ in the transcription of anti-apoptotic proteins. delete NF-${\kappa}B$ activation was inhibited before TNF-$\alpha$ stimulation. as described above. $AD5I{\kappa}B{\alpha}$-SR-transduction inhibited TNF-$\alpha$-induced nuclear translocation of p65. TNF-$\alpha$-induced cell death and apoptosis increased after inhibition of TNF-$\alpha$-induced activation of NF-${\kappa}$ by methods. Conclusion: These results suggest that TNF-$\alpha$-induced activation of NF-${\kappa}B$ may be closely related to the acquisition of the resistance to TNF-$\alpha$-induced apoptosis in lung cancer cells. Therefore. blocking of NF-${\kappa}B$ pathway can be a useful therapeutic modality in the treatment of lung cancer.

• Journal of Chest Surgery
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• v.36 no.3
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• pp.150-156
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• 2003

Tricuspid regurgitation has been considered as a secondary lesion when it is combined with left valvular heart diseases. However, there have been some reports which show that tricuspid regurgitation keeps going and results in congestive heart failure even after a successful operation for left valvular heart disease. So far, there are no definite operation indications and predictive factors for the tricuspid re-gurgitation which is resulted from the left sided valvular heart disease. We designed this study to evaluate the effects of pulmonary artery pressure and left ventricular ejection fraction on the prognosis of tricuspid regurgitation, and to make an operation indication for the patients with secondary tricuspid regurgitation. Material and Method: We reviewed the medical records of patients who underwent surgery for the left sided valvular heart disease with tricuspid regurgitation and were followed for more than 1 year with echocardiograms. There was a total of 114 cases. We compared the grades of tricuspid regurgitations and pulmonary artery pressures and left ventricular ejection fractions on the basis of echocardiograms which were checked preoperatively and on the last follow up. Result: There were 43 cases of tricuspid an-nuloplasty. In these patients, the grades of tricuspid regurgitations were improved in 42 cases (97.7%). But in 71 cases without annuloplasty, 29 cases (41%) were improved, 32 cases (45%) had no change, and 29 cases (14%) were aggravated. This finding shows significant differences in the prognoses of tricuspid regur-gitations between the two groups (p<0.05). There was no difference in pulmonary artery pressures and ejection fractions between the patients who showed progression of tricuspid regurgitations and those who didn't (p > 0.05). The improvements of tricuspid regurgitations are not statistically related to the changes of pulmonary artery pressures or left ventricular ejection fractions. Conclusion: This study shows that it is impossible to predict the prognoses of tricuspid regurgitations with preoperative pulmonary artery pressures or left ventricular ejection fractions. Also, the excellent results of tricuspid annuloplasty is proven in controlling the secondary tricuspid regurgitations. Therefore, when tricuspid regurgitation is detected preoperatively, the procedures to correct the tricuspid regurgitation at the time of the operation for the left-sided valvular heart disease must be considered positively, regardless of the grades of tricuspid regurgitations, to prevent sig-nificant tricuspid regurgitation that may develop later.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.1-19
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• 2018

Large amount of data is now available for research and business sectors to extract knowledge from it. This data can be in the form of unstructured data such as audio, text, and image data and can be analyzed by deep learning methodology. Deep learning is now widely used for various estimation, classification, and prediction problems. Especially, fashion business adopts deep learning techniques for apparel recognition, apparel search and retrieval engine, and automatic product recommendation. The core model of these applications is the image classification using Convolutional Neural Networks (CNN). CNN is made up of neurons which learn parameters such as weights while inputs come through and reach outputs. CNN has layer structure which is best suited for image classification as it is comprised of convolutional layer for generating feature maps, pooling layer for reducing the dimensionality of feature maps, and fully-connected layer for classifying the extracted features. However, most of the classification models have been trained using online product image, which is taken under controlled situation such as apparel image itself or professional model wearing apparel. This image may not be an effective way to train the classification model considering the situation when one might want to classify street fashion image or walking image, which is taken in uncontrolled situation and involves people's movement and unexpected pose. Therefore, we propose to train the model with runway apparel image dataset which captures mobility. This will allow the classification model to be trained with far more variable data and enhance the adaptation with diverse query image. To achieve both convergence and generalization of the model, we apply Transfer Learning on our training network. As Transfer Learning in CNN is composed of pre-training and fine-tuning stages, we divide the training step into two. First, we pre-train our architecture with large-scale dataset, ImageNet dataset, which consists of 1.2 million images with 1000 categories including animals, plants, activities, materials, instrumentations, scenes, and foods. We use GoogLeNet for our main architecture as it has achieved great accuracy with efficiency in ImageNet Large Scale Visual Recognition Challenge (ILSVRC). Second, we fine-tune the network with our own runway image dataset. For the runway image dataset, we could not find any previously and publicly made dataset, so we collect the dataset from Google Image Search attaining 2426 images of 32 major fashion brands including Anna Molinari, Balenciaga, Balmain, Brioni, Burberry, Celine, Chanel, Chloe, Christian Dior, Cividini, Dolce and Gabbana, Emilio Pucci, Ermenegildo, Fendi, Giuliana Teso, Gucci, Issey Miyake, Kenzo, Leonard, Louis Vuitton, Marc Jacobs, Marni, Max Mara, Missoni, Moschino, Ralph Lauren, Roberto Cavalli, Sonia Rykiel, Stella McCartney, Valentino, Versace, and Yve Saint Laurent. We perform 10-folded experiments to consider the random generation of training data, and our proposed model has achieved accuracy of 67.2% on final test. Our research suggests several advantages over previous related studies as to our best knowledge, there haven't been any previous studies which trained the network for apparel image classification based on runway image dataset. We suggest the idea of training model with image capturing all the possible postures, which is denoted as mobility, by using our own runway apparel image dataset. Moreover, by applying Transfer Learning and using checkpoint and parameters provided by Tensorflow Slim, we could save time spent on training the classification model as taking 6 minutes per experiment to train the classifier. This model can be used in many business applications where the query image can be runway image, product image, or street fashion image. To be specific, runway query image can be used for mobile application service during fashion week to facilitate brand search, street style query image can be classified during fashion editorial task to classify and label the brand or style, and website query image can be processed by e-commerce multi-complex service providing item information or recommending similar item.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.97-117
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• 2020

Product evaluation criteria is an indicator describing attributes or values of products, which enable users or manufacturers measure and understand the products. When companies analyze their products or compare them with competitors, appropriate criteria must be selected for objective evaluation. The criteria should show the features of products that consumers considered when they purchased, used and evaluated the products. However, current evaluation criteria do not reflect different consumers' opinion from product to product. Previous studies tried to used online reviews from e-commerce sites that reflect consumer opinions to extract the features and topics of products and use them as evaluation criteria. However, there is still a limit that they produce irrelevant criteria to products due to extracted or improper words are not refined. To overcome this limitation, this research suggests LDA-k-NN model which extracts possible criteria words from online reviews by using LDA and refines them with k-nearest neighbor. Proposed approach starts with preparation phase, which is constructed with 6 steps. At first, it collects review data from e-commerce websites. Most e-commerce websites classify their selling items by high-level, middle-level, and low-level categories. Review data for preparation phase are gathered from each middle-level category and collapsed later, which is to present single high-level category. Next, nouns, adjectives, adverbs, and verbs are extracted from reviews by getting part of speech information using morpheme analysis module. After preprocessing, words per each topic from review are shown with LDA and only nouns in topic words are chosen as potential words for criteria. Then, words are tagged based on possibility of criteria for each middle-level category. Next, every tagged word is vectorized by pre-trained word embedding model. Finally, k-nearest neighbor case-based approach is used to classify each word with tags. After setting up preparation phase, criteria extraction phase is conducted with low-level categories. This phase starts with crawling reviews in the corresponding low-level category. Same preprocessing as preparation phase is conducted using morpheme analysis module and LDA. Possible criteria words are extracted by getting nouns from the data and vectorized by pre-trained word embedding model. Finally, evaluation criteria are extracted by refining possible criteria words using k-nearest neighbor approach and reference proportion of each word in the words set. To evaluate the performance of the proposed model, an experiment was conducted with review on '11st', one of the biggest e-commerce companies in Korea. Review data were from 'Electronics/Digital' section, one of high-level categories in 11st. For performance evaluation of suggested model, three other models were used for comparing with the suggested model; actual criteria of 11st, a model that extracts nouns by morpheme analysis module and refines them according to word frequency, and a model that extracts nouns from LDA topics and refines them by word frequency. The performance evaluation was set to predict evaluation criteria of 10 low-level categories with the suggested model and 3 models above. Criteria words extracted from each model were combined into a single words set and it was used for survey questionnaires. In the survey, respondents chose every item they consider as appropriate criteria for each category. Each model got its score when chosen words were extracted from that model. The suggested model had higher scores than other models in 8 out of 10 low-level categories. By conducting paired t-tests on scores of each model, we confirmed that the suggested model shows better performance in 26 tests out of 30. In addition, the suggested model was the best model in terms of accuracy. This research proposes evaluation criteria extracting method that combines topic extraction using LDA and refinement with k-nearest neighbor approach. This method overcomes the limits of previous dictionary-based models and frequency-based refinement models. This study can contribute to improve review analysis for deriving business insights in e-commerce market.

• Journal of Nutrition and Health
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• v.42 no.8
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• pp.770-783
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• 2009

The school foodservice was quantitatively extended by policy of government all the while. There was carried out the survey of customer satisfaction about school foodservice by the ministry of education, science, and technology since 2006 years. Therefore, the purpose of this study was to grasp an improvement of the scores of school foodservice' quality attributes and satisfaction as compared with the preceding year by respondents and school type (elementary school, middle school, and high school). An annual survey was practiced to respondents (students, parents, and faculty) on september 2007 years and 2008 years in 16 cities and provinces. The statistics was analyzed to descriptive analysis and t-test for SPSS 12.0. The scores of school foodservice' quality attributes and overall customer satisfaction were almost increased to students, parents, and faculty and especially, big elevation in middle school. There was big increased the quality attributes such as 'providing information on foodservice', 'pleasant foodservice environment', 'kindness offered by employee' in elementary school, middle school, and high school to total respondents. An overall satisfaction in school foodservice was improved from 69.2 score to 71.9 score. On students, scores of overall satisfaction was increased from 72.9 to 74.0 as students of elementary school and from 61.5 to 65.8 as students of middle school (p < .001). Therefore, for improvement and development of school foodservice, there should be a necessary for an operator of school foodservice and an office of education to make an effort.

• Tuberculosis and Respiratory Diseases
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• v.48 no.5
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• pp.766-772
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• 2000

Background : Pressure rise time (PRT) is the time in which the ventilator aclieves the set airway pressure in pressure-targeted modes, such as pressure control ventilation (PCV). With varying PRT, in principle, the peak inspiratory flow rate of the ventilator also varies. And if PRT is set to a shorter duration, the effective duration of target pressure level would be prolonged, which in turn would increase inspiratory tidal volume(Vti) and mean airway pressure (Pmean). We also postulated that the increase in Vti with shortening of PRT may relate inversely to the patients' basal airway resistance. Methods : In 13 paralyzed patients on PCV (pressure control 18$\pm$9.5 cm $H_2O$ $FIO_2\;0.6\pm0.3$, PEEP 5$\pm$3 cm $H_2O$, f 20/min, I : E1 : 2) with Servo 300 (Siemens-Elema, Solna, Sweden) from various causes of respiratory failure, PRT of 10 %, 5 % and 0 % were randomly applied. At 30 min of each PRT trial, peak inspiratory flow (PIF, L/sec), Vti (ml), Pmean (cm $H_2O$) and ABGA were determined. Results : At PRT 10%, 5%, and 0%, PIF were 0.69$\pm$0.13, 0.77$\pm$0.19, 0.83$\pm$0.22, respectively (p<0.001). Vti were 425$\pm$94, 439$\pm$101, 456$\pm$106, respectively (p<0.001), and Pmean were 11.2$\pm$3.7, 12.0$\pm$3.7, 12.5$\pm$3.8, respectively (p<0.001). pH were 7.40$\pm$0.08, 7.40$\pm$0.92, 7.41$\pm$0.96, respectively (p=0.00) ; $PaCO_2$ (mm Hg) were 47.4$\pm$15.8, 47.2 $\pm$15.7, 44.6$\pm$16.2, respectively (p=0.004) ; $PAO_2-PaO_2$ (mm Hg) were 220$\pm$98, 224$\pm$95, 227$\pm$94, respectively (p=0.004) ; and $V_n/V_T$ as determined by ($PaCO_2-P_E-CO_2$)/$PaCO_2$ were 0.67$\pm$0.07, 0.67$\pm$0.08, 0.66$\pm$0.08, respectively (p=0.007). The correlation between airway resistance and change of Vti from PRT 10% to 0% were r= -0.243 (p=0.498). Conclusion : Shortening of pressure rise timee during PCV was associated with increased tidal volume, increased mean airway pressure and lower $PaCO_2$.

• Biomedical Science Letters
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• v.2 no.2
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• pp.133-151
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• 1996

After cardiac surgery, it has been recognized that various complications were associated with injured humoral and cellular immunity by cardiopulmonary bypass(CPB). Especially, in postoperative pulmonary dysfunction, transpulmonary leukostasis followed complement activation and inflammatory responses are major pathogen. Some studies have showed that pretreated-corticosteroids before CPB protected postoperative pulmonary dysfunction. Corticosteroids may inhibit complement and leukocyte activation. On based previous studies, present investigator determined changes of leukocyte counts and transpulmonary leukostasis during cardiac surgery and postoperative periods. For the evaluation of postoperative pulmonary function and edema, $PaO_2$ and chest X-ray were compared between pre-CPB and post-CPB. Fever and other parameters were also observed postoperatively. The aim of this study was to define for the prophylactic effects of corticosteroid(Solu-Medrol: 30mg/kg) on all the researched parameters. This study was prospectively designed with randomized-blind fashion for 50 patients undergoing cardiac surgery. According to the purpose of study, all patients were divided into placebo and steroid group. : Placebo group was 25 patients received normal saline(not corticosteroid), and steroid group was 25patients received corticosteroid(Solu-Medrol: 30mg/kg) before initiation of CPB. The results of study were summarized as follows. 1. Total peripheral leukocyte counts decreased significantly at 5 minutes of CPB in all patients(P<0.01), and began to increase progressively at later periods of CPB with neutrophilia. The significant rise remained at postoperative 7th day(P<0.05). 2. During partial CPB, transpulmonary leukostasis occurred in placebo group(P<0.001), whereas it was prevented in steroid group. 3. In both groups, peripheral lymphocyte counts were stable during CPB, but began to reduce at time of intensive care unit(ICU) and the lymphocytopenia remained until postoperative 3rd day. The lymphocyte counts recovered on postoperative 7th day. 4. In both groups, peripheral counts of monocyte were relatively stable in the early peroid of CPB, and increased gradually in the later periods of CPB. This significant monocytosis remained throughout postoperlative periods(P<0.05). 5. The mean value of postoperative $paO)_2$ was lower than that of pre-CPB in placebo group(P=0.01) but didn't significant in steroid group(P=0.90). In the incidence of pulmonary edema signs and fever, placebo group was higher than steroid group(P=0.001, p=0.01, respectively). However mechanical respiratory supporting and care periods at intensive care unit were not significant difference between two groups(P>.0.05).With the above results, the investigator concluded that leukocyte activation and pulmonary sequestration were caused by cardiac surgery with CPB and demonstrated that high dose corticosteroid will provide prophylactic effect for pulmonary leukostasis and higher neutrophilia. These effects may ameliorate postoperative pulmonary dysfunction and contribute to postoperative less morbidity. However, further study should be performed because postoperative lymphocytopenia continued for 3 days in both groups, which may suspected damage or suppression of cell-mediated immunity with used corticosteroid.

• Korean Journal of Organic Agriculture
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• v.27 no.3
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• pp.365-380
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• 2019

Total of 20 Holstein calves of 10 calves (3.90±0.26 month of age) born in spring (S) and 10 calves (4.10±0.30 month of age) born in fall (F) were reared in this study for 24 months and diets were divided into separate feeding of forage and concentrates (C) and TMR (T). Therefore, 4 treatments in this study were composed of CS, CF, TS and TF with the factors of diets and calving season. After parturition of heifers, all animals were fed the same diet and milk production was recorded monthly. DM intakes in growing period were influenced by calving season, and those of the animals calved in fall were higher than in those calved in spring (P<0.01), but there were no significant differences by feeding method. CP intakes and TDN intakes were significantly influenced by calving season (P<0.05) and feeding method (P<0.001), and the animals calved in fall were about 1.2% higher than those calved in spring, and the animals fed TMR were about 4.7% higher than those fed concentrates and forage separately. Average, 9th and 10th months' milk yields were significantly influenced by feeding method in which those in the treatments fed TMR (TS, TF) were higher than in separate feeding of concentrates and forage (CS, CF; average P<0.05; 9th and 10th months P<0.01). Average milk persistency was also significantly influenced by calving season (P<0.05) and feeding method (P<0.01) and those in the animals calved in fall were higher than in spring and those of the TMR fed animals were also higher than in separate feeding of concentrates and forage. Milk persistency was similar to the results of milk yield, showing statistically significant differences affected by the feeding method at 9th and 10th months of late lactation (P<0.01), and it was about 8% higher in the animals fed TMR, showing higher tendency at 7th (P=0.12) and 8th months of late lactation (P=0.09). Therefore, it is expected that postpartum milk yield and milk persistency would be higher when the hiefers are fed TMR in growing period and calved in fall. Average milk fat content was influenced by feeding method. Milk fat content of the animals fed TMR during growing period were 7.8% higher than those fed concentrates and forage separately (P<0.01). This suggests that feeding TMR during growing period influenced first postpartum eating behavior, which stabilized the rumen and resulted in the increased milk fat. At 3rd month after calving, milk fat content was lower in the animals calved in spring than in those calved in fall, suggesting that it might have been influenced by the seasonal differences. MUN showed significant differences by feeding method in which those in separate feeding of concentrates and forages were higher especially in average, 4th, 5th and 6th months (average and 4th P<0.01; 5th and 6th months P<0.05). SCC was higher in the animals fed TMR than in those fed concentrates and forage separately especially in average, 3rd and 4th months after calving (P<0.01). In conclusion, when feeding TMR during growing period and calving in fall, it was not influenced by the high temperature in summer, and it resulted in the improved milk yield, milk persistency and milk fat content.

• Journal of architectural history
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• v.14 no.1 s.41
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• pp.89-105
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• 2005

The central aim of this thesis is to see if the structure of Palsangjeon(捌相殿) in Pubjoo Temple(法住寺), a five sto wooden pagoda in Chosen(朝鮮) Dynasty, was handed down from the ancient and middle ages. This study was performed through an analysis of Gilt-Bronze Pagoda built in Koryo(高麗) period. In other words, it is aimed at analyzing which lineage the structure of Palsangjeonbelongs to as a wooden pagoda. In analyzing the structure of Palsangjeon, I attempted to find out its source from the remains of Koryo period prior to the Chosen Dynasty. Examples are the Gilt-Bronze Pagoda, built during the Koryo period. I have also examined its relationship with other existing wooden pagodas and remains. The analysis of Palsangjeon, a five story wooden pagoda in Chosen Dynasty, focuses on the following: First, I explored the possibilities of whether the structure of Palsangjeon was newly invented in Chosen Dynasty, or if it had been derived from the wooden pagodas in the Koryo period. Secondly, I tried to find out if the stable vertical planes, with a great successive diminution ratio, were derived from the middle age, i.e. Koryo period. The results of the study of Palsangjeon through Gilt-Bronze Pagoda analysis are as follows: 1. The structure of Gilt-Bronze Pagoda, a wooden pagoda from the Koryo period, is roughly classified into the accumulation type, using pipe pillars, and the one story type using whole pillars. In the accumulation type, stories are connected in either a flat format or an intervening format. The Gilt-Bronze Pagoda is mainly composed of pipe pillars, with some whole pillars. However, the central pillar was omitted in the building structure. Generally, the upper and lower stories are connected by pipe pillars in a crutch format. All the pillars, whether they are pipe pillars or whole pillars, used Naiten(內轉) technology. The Eave supporter has the Haang type(下昻) and the Muhaang type(無下昻). In most cases, high balustrades are furnished, but few tables of high balustrades have been found. The slanting roof formats have been handed down from Paekche(百濟), Silla(新羅), or Koryo(高麗). However, the structure of the octagon is assumed to be derived from Koguryo(高句麗). The structure of the Gilt-Bronze Pagoda from the Koryo period is mainly composed of accumulated flat squares, with some spire types. intervening format, the structure of Palsangjeon used whole pillars in a half story format in which upper level side pillars are installed on the lower level tie beam. From the Bronze Pagoda from the Koryo period, we can assume that the half story format of wooden pagodas that has stable vertical planes with a great successive diminution ratio was created during the mid-Koryo period at the latest and had been idly developed by the time of the Chosen Dynasty. 3. The whole pillars in Palsangjeon are also found in Gilt-Bronze Pagodas from the Koryo period. Hence, all of the pillars in Palsangjeon seem to have been handed down from the ancient construction technology. They were also used in the construction of wooden pagodas from the Koryo period. Therefore, it is assumed that Palsangjeon was constructed using the construction technology of the Chosen Dynasty that had been developed from the wooden pagoda construction technology of the Koryo period. The stable vertical planes with a great successive diminution ratio in Palsangjeon are derived from ancient Korean wooden pagodas, which have developed into indigenous Korean wooden pagodas with fairly stable vertical planes and a great design, in the half story format of Koryo and Chosen Dynasty. Therefore, it is assumed that the structure of Palsangjeon has a systematic relationship with traditional Korean wooden pagodas and is one of the indigenous Korean wooden pagoda structures. 4. In China, the intervening format has been mainly used between stories in multi-story architecture since the ancient days. At the same time, the flat format as also used in ancient and middle ages. However, the flat format was replaced by whole pillars during the Ming(明) and Manchu(淸) Dynasties, in favor of simple and compact construction. The half-story format, in which upper level side pillars are installed on tie beams, has been found in some cases, but it doesn't seem to have been the primary construction technology. Few traces of the half-story format have been found in multi-story architecture in Japan, and it has not been used as a general construction format. By contrast, the half-story format, which seems to have been derived from the Koryo period, was used as a general construction format in multi-story architecture of the Chosen Dynasty. The construction technology of multi-story architecture is related to that of multi-story wooden pagodas, but they have different production technologies. It seems that the structure of Palsangjeon did not just adopt the construction technology of multi-story architecture in the Chosen Dynasty, but it was developed from wooden pagodas in the Koryo period, including the Gilt-Bronze Pagoda. 5. Since the ancient days, most Chinese and Japanese wooden pagodas have adopted an accumulation type of structure using pipe pillars, with accumulated pointed towers. On the other hand, though most Korean wooden pagodas have also adopted an accumulation type of structure from the ancientdays, one story type using whole pillars was created in the Koryo and Chosen Dynasties. The wooden pagoda structure of Palsangjeon, with stable vertical planes in a half story format, is a unique Korean construction technology, different from the construction technologies of Chinese and Japanese wooden pagodas. This thesis clearly determined the structural characteristics of Palsangjeon. However, various remains have yet to be analyzed in depth, to establish an accurate construction technology system. In the beginning of this thesis, I had difficulty in precisely interpreting the internal structure of the Gilt-Bronze Pagoda from its appearance. However, in the process of study, the more serious problem was that there are few remains or ruins of multi-story architecture in ancient and the middle ages of Korea. Therefore, it is urgent to discover various remains in the future. This thesis succeeded in determining the structural characteristics of Palsangjeon. However, it fell short of clarifying the structural lineage of the stable vertical planes, although they show indigenous Korean architectural taste, representing the unique national emotion, and the construction format of multi-story wooden pagodas in Korea. I hope this is clarified in the future research.

• Asia pacific journal of information systems
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• v.21 no.1
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• pp.103-122
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• 2011

Recently, numerous documents have been made available electronically. Internet search engines and digital libraries commonly return query results containing hundreds or even thousands of documents. In this situation, it is virtually impossible for users to examine complete documents to determine whether they might be useful for them. For this reason, some on-line documents are accompanied by a list of keywords specified by the authors in an effort to guide the users by facilitating the filtering process. In this way, a set of keywords is often considered a condensed version of the whole document and therefore plays an important role for document retrieval, Web page retrieval, document clustering, summarization, text mining, and so on. Since many academic journals ask the authors to provide a list of five or six keywords on the first page of an article, keywords are most familiar in the context of journal articles. However, many other types of documents could not benefit from the use of keywords, including Web pages, email messages, news reports, magazine articles, and business papers. Although the potential benefit is large, the implementation itself is the obstacle; manually assigning keywords to all documents is a daunting task, or even impractical in that it is extremely tedious and time-consuming requiring a certain level of domain knowledge. Therefore, it is highly desirable to automate the keyword generation process. There are mainly two approaches to achieving this aim: keyword assignment approach and keyword extraction approach. Both approaches use machine learning methods and require, for training purposes, a set of documents with keywords already attached. In the former approach, there is a given set of vocabulary, and the aim is to match them to the texts. In other words, the keywords assignment approach seeks to select the words from a controlled vocabulary that best describes a document. Although this approach is domain dependent and is not easy to transfer and expand, it can generate implicit keywords that do not appear in a document. On the other hand, in the latter approach, the aim is to extract keywords with respect to their relevance in the text without prior vocabulary. In this approach, automatic keyword generation is treated as a classification task, and keywords are commonly extracted based on supervised learning techniques. Thus, keyword extraction algorithms classify candidate keywords in a document into positive or negative examples. Several systems such as Extractor and Kea were developed using keyword extraction approach. Most indicative words in a document are selected as keywords for that document and as a result, keywords extraction is limited to terms that appear in the document. Therefore, keywords extraction cannot generate implicit keywords that are not included in a document. According to the experiment results of Turney, about 64% to 90% of keywords assigned by the authors can be found in the full text of an article. Inversely, it also means that 10% to 36% of the keywords assigned by the authors do not appear in the article, which cannot be generated through keyword extraction algorithms. Our preliminary experiment result also shows that 37% of keywords assigned by the authors are not included in the full text. This is the reason why we have decided to adopt the keyword assignment approach. In this paper, we propose a new approach for automatic keyword assignment namely IVSM(Inverse Vector Space Model). The model is based on a vector space model. which is a conventional information retrieval model that represents documents and queries by vectors in a multidimensional space. IVSM generates an appropriate keyword set for a specific document by measuring the distance between the document and the keyword sets. The keyword assignment process of IVSM is as follows: (1) calculating the vector length of each keyword set based on each keyword weight; (2) preprocessing and parsing a target document that does not have keywords; (3) calculating the vector length of the target document based on the term frequency; (4) measuring the cosine similarity between each keyword set and the target document; and (5) generating keywords that have high similarity scores. Two keyword generation systems were implemented applying IVSM: IVSM system for Web-based community service and stand-alone IVSM system. Firstly, the IVSM system is implemented in a community service for sharing knowledge and opinions on current trends such as fashion, movies, social problems, and health information. The stand-alone IVSM system is dedicated to generating keywords for academic papers, and, indeed, it has been tested through a number of academic papers including those published by the Korean Association of Shipping and Logistics, the Korea Research Academy of Distribution Information, the Korea Logistics Society, the Korea Logistics Research Association, and the Korea Port Economic Association. We measured the performance of IVSM by the number of matches between the IVSM-generated keywords and the author-assigned keywords. According to our experiment, the precisions of IVSM applied to Web-based community service and academic journals were 0.75 and 0.71, respectively. The performance of both systems is much better than that of baseline systems that generate keywords based on simple probability. Also, IVSM shows comparable performance to Extractor that is a representative system of keyword extraction approach developed by Turney. As electronic documents increase, we expect that IVSM proposed in this paper can be applied to many electronic documents in Web-based community and digital library.