• Journal of Intelligence and Information Systems
• /
• v.24 no.2
• /
• pp.85-109
• /
• 2018

Recommender system recommends the items expected to be purchased by a customer in the future according to his or her previous purchase behaviors. It has been served as a tool for realizing one-to-one personalization for an e-commerce service company. Traditional recommender systems, especially the recommender systems based on collaborative filtering (CF), which is the most popular recommendation algorithm in both academy and industry, are designed to generate the items list for recommendation by using 'overall rating' - a single criterion. However, it has critical limitations in understanding the customers' preferences in detail. Recently, to mitigate these limitations, some leading e-commerce companies have begun to get feedback from their customers in a form of 'multicritera ratings'. Multicriteria ratings enable the companies to understand their customers' preferences from the multidimensional viewpoints. Moreover, it is easy to handle and analyze the multidimensional ratings because they are quantitative. But, the recommendation using multicritera ratings also has limitation that it may omit detail information on a user's preference because it only considers three-to-five predetermined criteria in most cases. Under this background, this study proposes a novel hybrid recommendation system, which selectively uses the results from 'traditional CF' and 'CF using multicriteria ratings'. Our proposed system is based on the premise that some people have holistic preference scheme, whereas others have composite preference scheme. Thus, our system is designed to use traditional CF using overall rating for the users with holistic preference, and to use CF using multicriteria ratings for the users with composite preference. To validate the usefulness of the proposed system, we applied it to a real-world dataset regarding the recommendation for POI (point-of-interests). Providing personalized POI recommendation is getting more attentions as the popularity of the location-based services such as Yelp and Foursquare increases. The dataset was collected from university students via a Web-based online survey system. Using the survey system, we collected the overall ratings as well as the ratings for each criterion for 48 POIs that are located near K university in Seoul, South Korea. The criteria include 'food or taste', 'price' and 'service or mood'. As a result, we obtain 2,878 valid ratings from 112 users. Among 48 items, 38 items (80%) are used as training dataset, and the remaining 10 items (20%) are used as validation dataset. To examine the effectiveness of the proposed system (i.e. hybrid selective model), we compared its performance to the performances of two comparison models - the traditional CF and the CF with multicriteria ratings. The performances of recommender systems were evaluated by using two metrics - average MAE(mean absolute error) and precision-in-top-N. Precision-in-top-N represents the percentage of truly high overall ratings among those that the model predicted would be the N most relevant items for each user. The experimental system was developed using Microsoft Visual Basic for Applications (VBA). The experimental results showed that our proposed system (avg. MAE = 0.584) outperformed traditional CF (avg. MAE = 0.591) as well as multicriteria CF (avg. AVE = 0.608). We also found that multicriteria CF showed worse performance compared to traditional CF in our data set, which is contradictory to the results in the most previous studies. This result supports the premise of our study that people have two different types of preference schemes - holistic and composite. Besides MAE, the proposed system outperformed all the comparison models in precision-in-top-3, precision-in-top-5, and precision-in-top-7. The results from the paired samples t-test presented that our proposed system outperformed traditional CF with 10% statistical significance level, and multicriteria CF with 1% statistical significance level from the perspective of average MAE. The proposed system sheds light on how to understand and utilize user's preference schemes in recommender systems domain.

• Journal of Intelligence and Information Systems
• /
• v.25 no.1
• /
• pp.21-41
• /
• 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 Society for Marine Environment & Energy
• /
• v.19 no.4
• /
• pp.322-331
• /
• 2016

Oil budget calculator identifies the removal pathways of spilled oil by both natural and response methods, and estimates the remaining oil required response activities. A oil budget calculator was newly developed as a response tool for Deepwater Horizon oil spill incident in Gulf of Mexico in 2010 to inform clean up decisions for Incident Comment System, which was also successfully utilized to media and general public promotion of oil spill response activities. This study analyzed the theoretical background of the oil budget calculator and explored its future application to Korea. The oil budge calculation of four catastrophic marine pollution incidents indicates that 3~8% of spilled oil was removed mechanically by skimmers, 1~5% by in-situ burning, 4.8~16% by chemical dispersion due to dispersant operation, and 37~56% by weathering processes such as evaporation, dissolution, and natural dispersion. The results show that in-situ burning and chemical dispersion effectively remove spilled oil more than the mechanical removal by skimming, and natural weathering processes are also very effective to remove spilled oil. To apply the oil budget calculator in Korea, its parameters need to be optimized in response to the seasonal characteristics of marine environment, the characteristics of spilled oil and response technologies. A new algorithm also needs to be developed to estimate the oil budget due to shoreline cleanup activities. An oil budget calculator optimized in Korea can play a critical role in informing decisions for oil spill response activities and communicating spill prevention and response activities with the media and general public.

• Management & Information Systems Review
• /
• v.37 no.1
• /
• pp.139-154
• /
• 2018

R programming is free and open source system associated with a rich and ever-growing set of libraries of functions developed and submitted by independent end-users. It is recognized as a popular tool for handling big data sets and analyzing them. Reflecting these characteristics, R has been gaining popularity from data analysts. However, the antecedents of R technology acceptance has not been studied yet. In this study we identify and investigates cognitive factors contributing to build user acceptance toward R in education environment. We extend the existing technology acceptance model by incorporating social norms and software capability. It was found that the factors of subjective norm, perceived usefulness, ease of use affect positively on the intention of acceptance R programming. In addition, perceived usefulness is related to subjective norms, perceived ease of use, and software capability. The main difference of this research from the previous ones is that the target system is not a stand-alone. In addition, the system is not static in the sense that the system is not a final version. Instead, R system is evolving and open source system. We applied the Technology Acceptance Model (TAM) to the target system which is a platform where diverse applications such as statistical, big data analyses, and visual rendering can be performed. The model presented in this work can be useful for both colleges that plan to invest in new statistical software and for companies that need to pursue future installations of new technologies. In addition, we identified a modified version of the TAM model which is extended by the constructs such as subjective norm and software capability to the original TAM model. However one of the weak aspects that might inhibit the reliability and validity of the model is that small number of sample size.

• The Korean Journal of Nuclear Medicine Technology
• /
• v.13 no.1
• /
• pp.9-14
• /
• 2009

Purpose: Nowadays in the nuclear medicine, many studies and efforts are being made to reduce the scan time, as well as the waiting time to be needed to execute exams after injection of radionuclide medicines. Several methods are being used in clinic, such as developing new radionuclide compounds that enable to be absorbed into target organs more quickly and reducing acquisition scan time by increase the number of Gamma Camera detectors to examine. Each medical equipment manufacturer has improved the imaging process techniques to reduce scan time. In this paper, we tried to analyze the difference of image quality between FBP, 3D OSEM reconstruction methods that commercialized and being clinically applied, and Astonish reconstruction method (A kind of Iterative fast reconstruction method of Philips), also difference of image quality on scan time. Material and Methods: We investigated in 32 patients that examined the Bone SPECT from June to July 2008 at department of nuclear medicine, ASAN Medical Center in Seoul. 40sec/frame and 20sec/frame images were acquired that using Philips‘ PRECEDENCE 16 Gamma Camera and then reconstructed those images by using the Astonish (Philips’ Reconstruction Method), 3D OSEM and FBP methods. The blinded test was performed to the clinical interpreting physicians with all images analyzed by each reconstruction method for qualitative analysis. And we analyzed target to non target ratio by draws lesions as the center of disease for quantitative analysis. At this time, each image was analyzed with same location and size of ROI. Results: In a qualitative analysis, there was no significant difference by acquisition time changes in image quality. In a quantitative analysis, the images reconstructed Astonish method showed good quality due to better sharpness and distinguish sharply between lesions and peripheral lesions. After measuring each mean value and standard deviation value of target to non target ratio with 40 sec/frame and 20sec/frame images, those values are Astonish (40 sec-$13.91{\pm}5.62$ : 20 sec-$13.88{\pm}5.92$), 3D OSEM (40 sec-$10.60{\pm}3.55$ : 20 sec-$10.55{\pm}3.64$), FBP (40 sec-$8.30{\pm}4.44$ : 20 sec-$8.19{\pm}4.20$). We analyzed target to non target ratio from 20 sec and 40 sec images. And we analyzed the result, In Astonish (t=0.16, p=0.872), 3D OSEM (t=0.51, p=0.610), FBP (t=0.73, p=0.469) methods, there was no significant difference statistically by acquisition time change in image quality. But FBP indicates no statistical differences while some images indicate difference between 40 sec/frame and 20 sec/frame images by various factors. Conclusions: In the circumstance, try to find a solution to reduce nuclear medicine scan time, the development of nuclear medicine equipment hardware has decreased while software has marched forward at a relentless. Due to development of computer hardware, the image reconstruction time was reduced and the expanded capacity to restore enables iterative methods that couldn't be performed before due to technical limits. As imaging process technique developed, it reduced scan time and we could observe that image quality keep similar level. While keeping exam quality and reducing scan time can induce the reduction of patient's pain and sensory waiting time, also accessibility of nuclear medicine exam will be improved and it provide better service to patients and clinical physician who order exams. Consequently, those things make the image of department of nuclear medicine be improved. Concurrent Imaging - A new function that setting up each image acquisition parameter and enables to acquire images simultaneously with various parameters to once examine.

• 한국지구물리탐사학회:학술대회논문집
• /
• 2000.09a
• /
• pp.54-69
• /
• 2000

There are groundwater trouble by high-salinity yield inducing sea-water intrusion in Cheju Island. It is used groundwater-GIS(Well-lnfo) in the maintenance and management of groundwater in Cheju Island to grasp groundwater trouble area and cause of high-salinity yield. For 16 wells certain to yield high-salinity, we logged specific electrical conductivity(EC) and tried to get hold of freshwater and saltwater relationship. As result of distribution of $Cl^-$ by depth, it is showed up groundwater trouble by high-salinity yield in the east coastal area and the partly north coastal area. The reason of high-salinity groundwater yield are low-groundwater level by the structure of geology and low-hydraulic gradient etc. There is necessity for management to development and use of groundwater in the high-salinity area, special management area.

• The Korean Journal of Nuclear Medicine Technology
• /
• v.19 no.1
• /
• pp.12-16
• /
• 2015

Purpose Principal component analysis (PCA) is a method often used in the neuroimagre analysis as a multivariate analysis technique for describing the structure of high dimensional correlation as the structure of lower dimensional space. PCA is a statistical procedure that uses an orthogonal transformation to convert a set of observations of correlated variables into a set of values of linearly independent variables called principal components. In this study, in order to investigate the usefulness of PCA in the brain PET image analysis, we tried to analyze C[11]-PIB PET image as a representative case. Materials and Methods Nineteen subjects were included in this study (normal = 9, AD/MCI = 10). For C[11]-PIB, PET scan were acquired for 20 min starting 40 min after intravenous injection of 9.6 MBq/kg C[11]-PIB. All emission recordings were acquired with the Biograph 6 Hi-Rez (Siemens-CTI, Knoxville, TN) in three-dimensional acquisition mode. Transmission map for attenuation-correction was acquired using the CT emission scans (130 kVp, 240 mA). Standardized uptake values (SUVs) of C[11]-PIB calculated from PET/CT. In normal subjects, 3T MRI T1-weighted images were obtained to create a C[11]-PIB template. Spatial normalization and smoothing were conducted as a pre-processing for PCA using SPM8 and PCA was conducted using Matlab2012b. Results Through the PCA, we obtained linearly uncorrelated independent principal component images. Principal component images obtained through the PCA can simplify the variation of whole C[11]-PIB images into several principal components including the variation of neocortex and white matter and the variation of deep brain structure such as pons. Conclusion PCA is useful to analyze and extract the main pattern of C[11]-PIB image. PCA, as a method of multivariate analysis, might be useful for pattern recognition of neuroimages such as FDG-PET or fMRI as well as C[11]-PIB image.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.21 no.12
• /
• pp.510-523
• /
• 2020

This study analyzed groundwater quality in hydroponic cultivation facilities. Through this study, the possibility of groundwater use was evaluated according to the quality of the groundwater for hydroponic cultivation facilities. Good groundwater quality, on average, is pH 6.61, EC 0.27 dS/m, NO3-N 7.64 mg/L, NH4+-N 0.80 mg/L, PO4-P 0.09 mg/L, K+ 6.26 mg/L, Ca2+ 18.57 mg/L, Mg2+ 4.38 mg/L, Na+ 20.85 mg/L, etc. All of these satisfy the water quality standard for raw water in nutrient cultivation. But in the case of farmers experiencing problems with groundwater quality, most of the items exceeded the water quality standard. As a result of the analysis, it was judged that purifying groundwater of unsuitable quality for crop cultivation, and using it as raw water, was effective in terms of water quality and soil purification. If an agricultural water purification system is constructed based on the results of this study, it is judged that the design will be easy because the items to be treated can be estimated. If a purification system is established, it can use groundwater directly in the facility and for horticulture. These study results will be available for use in sustainable agriculture and environments.

• International Commerce and Information Review
• /
• v.16 no.4
• /
• pp.409-437
• /
• 2014

The purpose of this study is to present the specific ways of successful localization by analyzing the success and failures case for localization within the framework of the strategic models through a theoretical background and strategic models of localization. The strategic models of localization are divided by management aspects such as the localization of product and sourcing, the localization of human resources, the localization of marketing, the localization of R&D, harmony with a local community and delegation of authority between headquarters and local subsidiaries. The results, by comparing and analyzing the success and failures case for localization of individual companies operating in India, indicate that in terms of localization of product and sourcing, there are successful companies which procure a components locally and produce a suitable model which local consumers prefer and the failed companies which can not meet local consumers' needs. In case of localization of human resources, most companies recognize the importance of this portion and make use of superior human resource aggressively through a related education. In case of localization of marketing, It is found that the successful companies perform pre-market research & management and build a effective marketing skills & after service network and select local business partner which has a technical skills and carry out a business activities, customer support, complaint handling with their own organization. In terms of localization of R&D, the successful major companies establish and operate R&D center to promote a suitable model for local customers. In part of harmony with a local community, it shows that companies which made a successful localization understand the cultural environment and contribute to the community through CSR. In aspect of delegation of authority between headquarters and local subsidiaries, it is found that most of Korean companies are very weak for this part. there is a tendency to be determined by the head office rather than local subsidiaries. Implication of this thesis is that Korean enterprises in India should carry forward localization of products and components, foster of local human resource who recognize management and system of company and take part in voluntary market strategy decision, wholly owned subsidiary, establishment and operation of R & D center, understanding of local culture and system, corporate social responsibility, autonomy in management.

• Archives of design research
• /
• v.18 no.4 s.62
• /
• pp.53-64
• /
• 2005

The emergence of new communication media, digital, is something of a wonder, as well as a cultural tension. The industrial technologies that dramatically expand human abilities are being developed much faster than the speed of adaptation by humans. Without an exception, it creates new contents and form of the culture by shaking the very foundation of the notion about human beings. Korean broadcasting environment has stepped into the era of multi-media, multi-channel as the digital technology separated the media into network, cable, satellite and internet. In this digital culture, broadcasting, as a medium of information delivering and communication, has bigger influence than ever. Such changes in broadcasting environment turned the TV viewers into new consumers who participate and play the main role in active communication by choosing and using the media. This study is trying to systemize the question about the core identity of broadcasting through brand as the consumers stand in the center of broadcasting with the power to select channel. The story schema theory can be applied as a cognitive psychological tool to approach the active consumers in order to explain the cognitive processes that are related to information processing. It is a design with stories, which comes up as a case of a brand's story telling. The range of this study covers the current issue and educational programs in network TV during the period of May and August of year 2005. The cases of Korean and foreign programs were compared by the station each program is broadcasted. This study concludes that it is important to take the channel identity into the consideration in the brand strategy of each program. Especially, the leading programs of a station must not be treated as a separate program that has nothing to do with the station's identity. They must be treated to include the contents and form that builds the identity of the channel. Also, this study reconfirmed that building a brand of the anchor person can play as an important factor in the identity of the program's brand.