• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.135-149
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• 2020

Artificial intelligences are changing world. Financial market is also not an exception. Robo-Advisor is actively being developed, making up the weakness of traditional asset allocation methods and replacing the parts that are difficult for the traditional methods. It makes automated investment decisions with artificial intelligence algorithms and is used with various asset allocation models such as mean-variance model, Black-Litterman model and risk parity model. Risk parity model is a typical risk-based asset allocation model which is focused on the volatility of assets. It avoids investment risk structurally. So it has stability in the management of large size fund and it has been widely used in financial field. XGBoost model is a parallel tree-boosting method. It is an optimized gradient boosting model designed to be highly efficient and flexible. It not only makes billions of examples in limited memory environments but is also very fast to learn compared to traditional boosting methods. It is frequently used in various fields of data analysis and has a lot of advantages. So in this study, we propose a new asset allocation model that combines risk parity model and XGBoost machine learning model. This model uses XGBoost to predict the risk of assets and applies the predictive risk to the process of covariance estimation. There are estimated errors between the estimation period and the actual investment period because the optimized asset allocation model estimates the proportion of investments based on historical data. these estimated errors adversely affect the optimized portfolio performance. This study aims to improve the stability and portfolio performance of the model by predicting the volatility of the next investment period and reducing estimated errors of optimized asset allocation model. As a result, it narrows the gap between theory and practice and proposes a more advanced asset allocation model. In this study, we used the Korean stock market price data for a total of 17 years from 2003 to 2019 for the empirical test of the suggested model. The data sets are specifically composed of energy, finance, IT, industrial, material, telecommunication, utility, consumer, health care and staple sectors. We accumulated the value of prediction using moving-window method by 1,000 in-sample and 20 out-of-sample, so we produced a total of 154 rebalancing back-testing results. We analyzed portfolio performance in terms of cumulative rate of return and got a lot of sample data because of long period results. Comparing with traditional risk parity model, this experiment recorded improvements in both cumulative yield and reduction of estimated errors. The total cumulative return is 45.748%, about 5% higher than that of risk parity model and also the estimated errors are reduced in 9 out of 10 industry sectors. The reduction of estimated errors increases stability of the model and makes it easy to apply in practical investment. The results of the experiment showed improvement of portfolio performance by reducing the estimated errors of the optimized asset allocation model. Many financial models and asset allocation models are limited in practical investment because of the most fundamental question of whether the past characteristics of assets will continue into the future in the changing financial market. However, this study not only takes advantage of traditional asset allocation models, but also supplements the limitations of traditional methods and increases stability by predicting the risks of assets with the latest algorithm. There are various studies on parametric estimation methods to reduce the estimated errors in the portfolio optimization. We also suggested a new method to reduce estimated errors in optimized asset allocation model using machine learning. So this study is meaningful in that it proposes an advanced artificial intelligence asset allocation model for the fast-developing financial markets.

• Quality Improvement in Health Care
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• v.7 no.2
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• pp.138-155
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• 2000

Background: Factors related to waiting and staying time for patient care in emergency care center (ECC) were examined during 1 month from Apr. 1 to Apr. 30, 1997 at an ECC of Yeungnam university hospital in Taegu metropolitan city, to obtain the baseline data on the strategy of effective management of emergency patients. Method: The study subjects consisted of the 1,742 patients who visited at ECC and the data were obtained from the medical records of ECC and direct surveys. Results: The mean interval between ECC admission time and initial care time by each ECC duty residents was 83.1 minutes for male patients and 84.9 minutes for female patients, and mean ECC staying time (time interval between admission and final disposition from ECC) was 718.0 minutes in men and 670.5 minutes in women. As the results, the mean staying time in ECC was higher in older age, and especially the both of initial care time and staying time were highest in patients of medical aid, and shortest in patients of worker's accident compensation insurance. The on admission or not, previously endotracheal-intubation state of patient. The ECC staying ti initial care time was much more delayed in patients of not having previous medical records and the ECC staying time was higher in referred patients from out-patient department, in transferred patients from the other hospitals and patients having previous records, and in patients partly used the order-communicating system. The factors associated with the initial care time were the numbers of ECC patients and the existence of any true emergent patients, being cardiopulmonary resuscitation (CPR) statusme was much more longer in patients of drug intoxication, in CPR patients, in medical department patients, in transfused patients and in patients related to 3 or more departments. And according to the numbers of duty internships, the ECC staying time for four internships was more longer than for five internships and after admission ordering was done, also-more longer in status being of no available beds. As above mentioned results, the factors for the ECC staying time were thought to be statistically significant (P<0.01) according to the patient's age and the laboratory orders and the X-ray films checked. And also the factor for the ECC staying time were thought to be statistically significant (P<0.01) according to the status being of no available beds, the laboratory orders and/or the special laboratory orders, the X-ray films checked, final disposing department, transferred to other hospital or not, home medication or not, admission or not, the grades of beds, the year grades of residents, the causes of ECC visit, the being CPR status on admission or not, the surgical operation or not, being known personells in our hospital. Conclution: Authors concluded that the relieving method of long-staying time in ECC was being establishing the legally proved apparatus which could differentiate the true emergency or non-emergency patients, and that the methods of shortening ECC staying time were doing definitely necessary laboratory orders and managing beds more flexibly to admit for ECC patients and finally this methods were thought to be a method of unloading for ECC personnels and improving the quality of care in emergency patients.

• Proceedings of the Korean DIstribution Association Conference
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• 2005.05a
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• pp.383-405
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• 2005

The traditional market is foremost a regionally positioned place, wherein the market directly represents regional and cultural centered traits while it plays an important role in the circulation of facilities through reciprocal, informative and cultural exchanges while sewing to form local communities. The traditional market in Korea is one of representative retail businesses and premodern marketing techniques by family owned business of less than five members such as product management, purchase method, and marketing patterns etc. Since the 1990s, the appearance of new circulation-type businesses and large discount convenience stores escalated the loss of traditional competitiveness, increased the living standard of customers, changed purchasing patterns, and expanded the ubiquity of the Internet. All of these changes in external circulation circumstances have led the traditional markets to lose their place in the economy. The traditional market should revive on a regional site basis through the formation of a community of regional neighbors and through knowledge-sharing that leads to the creation of wealth. For the purpose of creating a wealth in a place, the following components are necessary: 1) a facility suitable for the spatial place of the present, 2)trust built through exchanges within the changing market environment, which would simultaneously satisfy customer's desires, 3) international bench marking on cases such as regionally centered TCM (England), BID (USA), and TMO (Japan) so that the market unit of store placement transfers from a spot policy to a line policy, 4)conversion of communicative conception through a surface policy approach centered around a macro-region perspective. The budget of the traditional market funding policy was operational between 2001 and 2004, serving as a counter move to solve the problem of the old traditional market through government intervention in regional economies to promote national economic strength. This national treasury funding project was centered on environmental improvement, research corps, and business modernization through the expenditure of 3,853 hundred million won (Korean currency). However, the effectiveness of this project has yet to be to proven through investigation. Furthermore, in promoting this funding support project, a lack of professionalism among merchants in the market led to constant limitations in comprehensive striving strategies, reduced capabilities in middle-and long-term plan setup, and created reductions in voluntary merchant agreement solutions. The traditional market should go beyond mere physical place and ordinary products creative site strategies employing the communicative approach must accompany these strategies to make the market a new regional and spatial living place. Thus, regarding recent paradigm changes and the introduction of region-based site functions into the traditional market, acquiring a conversion of direction into the newly developed project is essential to reinvestigate the traditional market composed of cultural and economic meanings, for the purpose of the research. Excavating social policy demands through the comparative analysis of domestic and international cases as well as innovative and expert management leadership development for NPO or NGO civil entrepreneurs through advanced case research on present promotion methods is extremely important. Discovering the seeds of the cultural contents industry cored around regional resource usages, commercializing regionally reknowned products, and constructing complex cultural living places for regional networks are especially important. In order to accelerate these solutions, a comprehensive and systemized approach research operated within a mentor academy system is required, as research will reveal distinctive traits of the traditional market in the aging society.

• Korean Journal of Ecology and Environment
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• v.45 no.2
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• pp.158-173
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• 2012

The objectives of this study were to analyze the longitudinal gradient and temporal variations of water quality in Daecheong Reservoir in relation to the major inflowing streams from the watershed, during 2001~2010. For the study, we selected 7 main-stream sites of the reservoir along the main axis of the reservoir, from the headwater to the dam and 8 tributary streams. In-reservoir nutrients of TN and TP showed longitudinal declines from the headwater to the dam, which results in a distinct zonation of the riverine ($R_z$, M1~M3), transition ($T_z$, M4~M6), and lacustrine zone ($L_z$, M7) in water quality, as shown in other foreign reservoirs. Chlorophyll-a (CHL) and BOD as an indicator of organic matter, were maximum in the $T_z$. Concentration of total phosphorus (TP) was the highest (8.52 $mg\;L^{-1}$) on March in the $R_z$, and was the highest (165 ${\mu}g\;L^{-1}$) in the $L_z$ on July. Values of TN was the maximum (377 ${\mu}g\;L^{-1}$) on August in the $R_z$, and was the highest (3.76 $mg\;L^{-1}$) in the $L_z$ on August. Ionic dilution was evident during September~October, after the monsoon rain. The mean ratios of TN : TP, as an indicator of limiting factor, were 88, which indicates that nitrogen is a surplus for phytoplankton growth in this system. Nutrient analysis of inflowing streams showed that major nutrient sources were headwater streams of T1~T2 and Ockcheon-Stream of T5, and the most influential inflowing stream to the reservoir was T5, which is located in the mid-reservoir, and is directly influenced by the waste-water treatment plants. The key parameters, influenced by the monsoon rain, were TP and suspended solids (SS). Empirical models of trophic variables indicated that variations of CHL in the $R_z$ ($R^2$=0.044, p=0.264) and $T_z$ ($R^2$=0.126, p=0.054) were not accounted by TN, but were significant (p=0.032) in the $L_z$. The variation of the log-transformed $I_r$-CHL was not accounted ($R^2$=0.258, p=0.110) by $I_w$-TN of inflowing streams, but was determined ($R^2$=0.567, p=0.005) by $I_w$-TP of inflowing streams. In other words, TP inputs from the inflowing streams were the major determinants on the in-reservoir phytoplankton growth. Regression analysis of TN : TP suggested that the ratio was determined by P, rather than N. Overall, our data suggest that TP and suspended solids, during the summer flood period, should be reduced from the eutrophication control and P-input from Ockcheon-Stream should be controlled for water quality improvement.

• Tuberculosis and Respiratory Diseases
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• v.43 no.6
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• pp.916-924
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• 1996

Bacground : Percutaneous needle aspiration biopsy (PCNA) is one of the most frequently used diagnostic methcxJs for intrathoracic lesions. Previous studies have reponed wide range of diagnostic yield from 28 to 98%. However, diagnostic yield has been increased by accumulation of experience, improvement of needle and the image guiding systems. We analysed the results of PCNA performed for one year to evaluate the diagnostic yield, the rate and severity of complications and factors affecting the diagnostic yield. Method : 287 PCNAs undergone in 236 patients from January, 1994 to December, 1994 were analysed retrospectively. The intrathoracic lesions was targeted and aspirated with 21 - 23 G Chiba needle under fluoroscopic guiding system. Occasionally, 19 - 20 G Biopsy gun was used for core tissue specimen. The specimen was requested for microbiologic, cytologic and histopathologic examination in the case of obtained core tissue. Diagnostic yields and complication rate of benign and malignant lesions were ca1culaled based on patients' chans. The comparison for the diagnostic yields according to size and shape of the lesions was analysed with chi square test (p<0.05). Results : There are 19.9% of consolidative lesion and 80.1% of nodular or mass lesion, and the lesion is located at the right upper lobe in 26.3% of cases, the right middle lobe in 6.4%, the right lower lobe 21.2%, the left upper lobe in 16.8%, the left lower lobe in 10.6%, and mediastinum in 1.3%. The lesion distributed over 2 lobes is as many as 17.4% of cases. There are 74 patients with benign lesions, 142 patients with malignant lesions in final diagnosis and confirmative diagnosis was not made in 22 patients despite of all available diagnostic methods. 2 patients have lung cancer and pulmonary tuberculosis concomittantly. Experience with 236 patients showed that PCNA can diagnose benign lesions in 62.2% (42 patients) of patients with such lesions and malignant lesions in 82.4% (117 patients) of patients. For the patients in whom the first PCNA failed to make diagnosis, the procedure was repeated and the cumulative diagnostic yield was increased as 44.6%, 60.8%, 62.2% in benign lesions and as 73.4%, 81.7%, 82.4% in malignant lesions through serial PCNA. Thoracotomy was performed in 9 patients with benign lesions and in 43 patients with malignant lesions. PCNA and thoracotomy showed the same pathologic result in 44.4% (4 patients) of benign lesions and 58.1% (25 patients) of malignant lesions. Thoracotomy confirmed 4 patients with malignat lesions against benign result of PCNA and 2 patients with benign lesions against malignant result of PCNA. There are 1.0% (3 cases) of hemoptysis, 19.2% (55 cases) of blood tinged sputum, 12.5% (36 cases) of pneumothorax and 1.0% (3 cases) of fever through 287 times of PCNA. Hemoptysis and blood tinged sputum didn't need therapy. 8 cases of pneumothorax needed insertion of classical chest tube or pig-tail catheter. Fever subsided within 48 hours in all cases. There was no difference between size and shape of lesion with diagnostic yield. Conclusion: PCNA shows relatively high diagnostic yield and mild degree complications but the accuracy of histologic diagnosis has to be improved.

• Korean Journal of Poultry Science
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• v.35 no.3
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• pp.291-302
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• 2008

To acquire essentially necessary basic data to establish feeding system by verifying appropriate dietary energy and protein level for the growth of commercial slow growing broiler chicks within the country, two experiments were conducted for 5 weeks. One day old, 1,404 male and female broiler chicks were used for the experiments, and 26 chicks were placed at each pen. The energy level of feed was maintained about 3,000 or 3,100 kg/kcal for whole breeding period of 5 weeks, and protein content was adjusted about 20, 21, and 22% during the first two weeks and the content was adjusted to 18, 19, 20, 21, and 22% from the 3 to 5 weeks old of the experiment. The categories of body weight and feed intake amount were monitored to calculate the productivity and blood sampling was conducted for the analysis at the end of each experiment. Experiment 1:Although the productivity by the ME content difference during $0{\sim}2$ weeks did not have significant difference and the body weight increase by the difference of CP content and feed intake amount did not have much difference, the feed requirement rate was statistically improved in CP 21 and 22% treatment groups compared to the CP 20% group (P<0.05). The feed ME 3,100 kcal/kg treated group during $3{\sim}5$ weeks after starting the experiment revealed to show improved feed requirement rate (P<0.05). Within the period of experiment, the CP 22% treated group resulted to show significant body weight increase compared to the groups treated with low levels of CP (P<0.05) and the feed requirement rate was improved in high CP treated group compared to low CP treated groups, but the feed intake amount did not show significant difference between treated groups. During the experiment period, the body weight increase and feed requirement rate revealed to interact between ME and CP (P<0.05). During the whole experiment period of the 5 weeks, the feed requirement rate was improved in ME 3,100 kcal/kg treated group than the groups treated with ME 3,000 kcal/kg, and the CP (20) 18% treatment groups resulted to show higher values than other treatment groups (P<0.05). Body weight increase was high in CP (22) 22% treated groups than those of CP (21) 21% and (20) 18% treated groups, and the interaction between ME and CP was found at body weight increase and feed requirement rate (P<0.05). Although blood albumin and total cholesterol levels were elevated in ME 3,100 kcal/kg treated group than ME 3,000 kcal/kg treated group, but neutral fat content was reduced (P<0.05). On the other hand, the total cholesterol content was increased in CP (22) 21% treated group than CP (22) 20% and CP (20) 18% treated groups (P<0.05). Experiment 2: The body weight increase in 0-2 weeks was higher in ME 3,100 kcal/kg treated group than ME 3,000 kcal/kg treated group, and it was highly improved in CP 22% treated group than CP 20% treated group by showing the interaction between CP and ME (P<0.05). The significant improvement of feed requirement rate was observed in CP 21% and 22% treated groups compared to CP 20% treated group (P<0.05). The productivity between the growth period from 3 to 5 weeks of age and whole growth period resulted to show no significant difference. Although no difference was observed in blood composition between treated groups, the interaction of ME and CP on cholesterol content was accepted at the range of P<0.05). Therefore, it is considered that the appropriate dietary protein level within feed for the physiology of growing broiler chicks was 22% or more for the first two weeks and protein level of 21% or 20% from 3 to 5 weeks old for the maximization of productivity. Even if the energy level within feed had some partial effects on the productivity, but did not show consistency. So, further experiments needto be conducted by differentiating the energy level.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.111-126
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• 2020

Most industries have recently become aware of the importance of customer lifetime value as they are exposed to a competitive environment. As a result, preventing customers from churn is becoming a more important business issue than securing new customers. This is because maintaining churn customers is far more economical than securing new customers, and in fact, the acquisition cost of new customers is known to be five to six times higher than the maintenance cost of churn customers. Also, Companies that effectively prevent customer churn and improve customer retention rates are known to have a positive effect on not only increasing the company's profitability but also improving its brand image by improving customer satisfaction. Predicting customer churn, which had been conducted as a sub-research area for CRM, has recently become more important as a big data-based performance marketing theme due to the development of business machine learning technology. Until now, research on customer churn prediction has been carried out actively in such sectors as the mobile telecommunication industry, the financial industry, the distribution industry, and the game industry, which are highly competitive and urgent to manage churn. In addition, These churn prediction studies were focused on improving the performance of the churn prediction model itself, such as simply comparing the performance of various models, exploring features that are effective in forecasting departures, or developing new ensemble techniques, and were limited in terms of practical utilization because most studies considered the entire customer group as a group and developed a predictive model. As such, the main purpose of the existing related research was to improve the performance of the predictive model itself, and there was a relatively lack of research to improve the overall customer churn prediction process. In fact, customers in the business have different behavior characteristics due to heterogeneous transaction patterns, and the resulting churn rate is different, so it is unreasonable to assume the entire customer as a single customer group. Therefore, it is desirable to segment customers according to customer classification criteria, such as loyalty, and to operate an appropriate churn prediction model individually, in order to carry out effective customer churn predictions in heterogeneous industries. Of course, in some studies, there are studies in which customers are subdivided using clustering techniques and applied a churn prediction model for individual customer groups. Although this process of predicting churn can produce better predictions than a single predict model for the entire customer population, there is still room for improvement in that clustering is a mechanical, exploratory grouping technique that calculates distances based on inputs and does not reflect the strategic intent of an entity such as loyalties. This study proposes a segment-based customer departure prediction process (CCP/2DL: Customer Churn Prediction based on Two-Dimensional Loyalty segmentation) based on two-dimensional customer loyalty, assuming that successful customer churn management can be better done through improvements in the overall process than through the performance of the model itself. CCP/2DL is a series of churn prediction processes that segment two-way, quantitative and qualitative loyalty-based customer, conduct secondary grouping of customer segments according to churn patterns, and then independently apply heterogeneous churn prediction models for each churn pattern group. Performance comparisons were performed with the most commonly applied the General churn prediction process and the Clustering-based churn prediction process to assess the relative excellence of the proposed churn prediction process. The General churn prediction process used in this study refers to the process of predicting a single group of customers simply intended to be predicted as a machine learning model, using the most commonly used churn predicting method. And the Clustering-based churn prediction process is a method of first using clustering techniques to segment customers and implement a churn prediction model for each individual group. In cooperation with a global NGO, the proposed CCP/2DL performance showed better performance than other methodologies for predicting churn. This churn prediction process is not only effective in predicting churn, but can also be a strategic basis for obtaining a variety of customer observations and carrying out other related performance marketing activities.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.19-33
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• 2013

In this research, a proposed Dynamic Virtual Ontology using Tags (DyVOT) supports dynamic search of resources depending on user's requirements using tags from social web driven resources. It is general that the tags are defined by annotations of a series of described words by social users who usually tags social information resources such as web-page, images, u-tube, videos, etc. Therefore, tags are characterized and mirrored by information resources. Therefore, it is possible for tags as meta-data to match into some resources. Consequently, we can extract semantic relationships between tags owing to the dependency of relationships between tags as representatives of resources. However, to do this, there is limitation because there are allophonic synonym and homonym among tags that are usually marked by a series of words. Thus, research related to folksonomies using tags have been applied to classification of words by semantic-based allophonic synonym. In addition, some research are focusing on clustering and/or classification of resources by semantic-based relationships among tags. In spite of, there also is limitation of these research because these are focusing on semantic-based hyper/hypo relationships or clustering among tags without consideration of conceptual associative relationships between classified or clustered groups. It makes difficulty to effective searching resources depending on user requirements. In this research, the proposed DyVOT uses tags and constructs ontologyfor effective search. We assumed that tags are extracted from user requirements, which are used to construct multi sub-ontology as combinations of tags that are composed of a part of the tags or all. In addition, the proposed DyVOT constructs ontology which is based on hierarchical and associative relationships among tags for effective search of a solution. The ontology is composed of static- and dynamic-ontology. The static-ontology defines semantic-based hierarchical hyper/hypo relationships among tags as in (http://semanticcloud.sandra-siegel.de/) with a tree structure. From the static-ontology, the DyVOT extracts multi sub-ontology using multi sub-tag which are constructed by parts of tags. Finally, sub-ontology are constructed by hierarchy paths which contain the sub-tag. To create dynamic-ontology by the proposed DyVOT, it is necessary to define associative relationships among multi sub-ontology that are extracted from hierarchical relationships of static-ontology. The associative relationship is defined by shared resources between tags which are linked by multi sub-ontology. The association is measured by the degree of shared resources that are allocated into the tags of sub-ontology. If the value of association is larger than threshold value, then associative relationship among tags is newly created. The associative relationships are used to merge and construct new hierarchy the multi sub-ontology. To construct dynamic-ontology, it is essential to defined new class which is linked by two more sub-ontology, which is generated by merged tags which are highly associative by proving using shared resources. Thereby, the class is applied to generate new hierarchy with extracted multi sub-ontology to create a dynamic-ontology. The new class is settle down on the ontology. So, the newly created class needs to be belong to the dynamic-ontology. So, the class used to new hyper/hypo hierarchy relationship between the class and tags which are linked to multi sub-ontology. At last, DyVOT is developed by newly defined associative relationships which are extracted from hierarchical relationships among tags. Resources are matched into the DyVOT which narrows down search boundary and shrinks the search paths. Finally, we can create the DyVOT using the newly defined associative relationships. While static data catalog (Dean and Ghemawat, 2004; 2008) statically searches resources depending on user requirements, the proposed DyVOT dynamically searches resources using multi sub-ontology by parallel processing. In this light, the DyVOT supports improvement of correctness and agility of search and decreasing of search effort by reduction of search path.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.21-41
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• 2019

Thanks to the rapid development of information technologies, the data available on Internet have grown rapidly. In this era of big data, many studies have attempted to offer insights and express the effects of data analysis. In the tourism and hospitality industry, many firms and studies in the era of big data have paid attention to online reviews on social media because of their large influence over customers. As tourism is an information-intensive industry, the effect of these information networks on social media platforms is more remarkable compared to any other types of media. However, there are some limitations to the improvements in service quality that can be made based on opinions on social media platforms. Users on social media platforms represent their opinions as text, images, and so on. Raw data sets from these reviews are unstructured. Moreover, these data sets are too big to extract new information and hidden knowledge by human competences. To use them for business intelligence and analytics applications, proper big data techniques like Natural Language Processing and data mining techniques are needed. This study suggests an analytical approach to directly yield insights from these reviews to improve the service quality of hotels. Our proposed approach consists of topic mining to extract topics contained in the reviews and the decision tree modeling to explain the relationship between topics and ratings. Topic mining refers to a method for finding a group of words from a collection of documents that represents a document. Among several topic mining methods, we adopted the Latent Dirichlet Allocation algorithm, which is considered as the most universal algorithm. However, LDA is not enough to find insights that can improve service quality because it cannot find the relationship between topics and ratings. To overcome this limitation, we also use the Classification and Regression Tree method, which is a kind of decision tree technique. Through the CART method, we can find what topics are related to positive or negative ratings of a hotel and visualize the results. Therefore, this study aims to investigate the representation of an analytical approach for the improvement of hotel service quality from unstructured review data sets. Through experiments for four hotels in Hong Kong, we can find the strengths and weaknesses of services for each hotel and suggest improvements to aid in customer satisfaction. Especially from positive reviews, we find what these hotels should maintain for service quality. For example, compared with the other hotels, a hotel has a good location and room condition which are extracted from positive reviews for it. In contrast, we also find what they should modify in their services from negative reviews. For example, a hotel should improve room condition related to soundproof. These results mean that our approach is useful in finding some insights for the service quality of hotels. That is, from the enormous size of review data, our approach can provide practical suggestions for hotel managers to improve their service quality. In the past, studies for improving service quality relied on surveys or interviews of customers. However, these methods are often costly and time consuming and the results may be biased by biased sampling or untrustworthy answers. The proposed approach directly obtains honest feedback from customers' online reviews and draws some insights through a type of big data analysis. So it will be a more useful tool to overcome the limitations of surveys or interviews. Moreover, our approach easily obtains the service quality information of other hotels or services in the tourism industry because it needs only open online reviews and ratings as input data. Furthermore, the performance of our approach will be better if other structured and unstructured data sources are added.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.32 no.1
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• pp.93-106
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• 2014

In this study, Analyze environment of location, investigation into vegetation resources, survey management status and establish to classify the management area for Natural monument No.374 Pyengdae-ri Torreya nucifera forest. The results were as follows: First, Torreya nucifera forest is concerned about influence of development caused by utilization of land changes to agricultural region. Thus, establish to preservation management plan for preservation of prototypical and should be excluded development activity to cause the change of terrain that Gotjawal in the Torreya nucifera forest is factor of base for generating species diversity. Secondly, Torreya nucifera forest summarized as 402 taxa composed 91 familly 263 genus, 353 species, 41 varieties and 8 forms. The distribution of plants for the first grade & second grade appear of endangered plant to Ministry of Environment specify. But, critically endangered in forest by changes in habitat, diseases and illegal overcatching. Therefore, when establishing forest management plan should be considered for put priority on protection. Thirdly, Torreya nucifera representing the upper layer of the vegetation structure. But, old tree oriented management and conservation strategy result in poor age structure. Furthermore, desiccation of forest on artificial management and decline in Torreya nucifera habitat on ecological succession can indicate a problem in forest. Therefore, establish plan such as regulation of population density and sapling tree proliferation for sustainable characteristics of the Torreya nucifera forest. Fourth, Appear to damaged of trails caused by use. Especially, Scoria way occurs a lot of damaged and higher than the share ratio of each section. Therefore, share ratio reduction Plan should be considered through the additional development of tourism routes rather than the replacement of Scoria. Fifth, Representing high preference of the Torreya nucifera forest tourist factor confirmed the plant elements. It is sensitive to usage pressure. And requires continuous monitoring by characteristic of Non-permanent. In addition, need an additional plan such as additional development of tourism elements and active utilizing an element of high preference. Sixth, Strength of protected should be differently accordance with importance. First grade area have to maintenance of plant population and natural habitats. Set the direction of the management. Second grade areas focus on annual regeneration of the forest. Third grade area should be utilized demonstration forest or set to the area for proliferate sapling. Fourth grade areas require the introduced of partial rest system that disturbance are often found in proper vegetation. Fifth grade area appropriate to the service area for promoting tourism by utilizing natural resources in Torreya nucifera forest. Furthermore, installation of a buffer zone in relatively low ratings area and periodic monitoring to the improvement of edge effect that adjacent areas of different class.