• Journal of Intelligence and Information Systems
• /
• v.26 no.2
• /
• pp.43-56
• /
• 2020

Recommender systems help users make the best choice among various options. Especially, recommender systems play important roles in internet sites as digital information is generated innumerable every second. Many studies on recommender systems have focused on an accurate recommendation. However, there are some problems to overcome in order for the recommendation system to be commercially successful. First, there is a lack of transparency in the recommender system. That is, users cannot know why products are recommended. Second, the recommender system cannot immediately reflect changes in user preferences. That is, although the preference of the user's product changes over time, the recommender system must rebuild the model to reflect the user's preference. Therefore, in this study, we proposed a recommendation methodology using topic modeling and sequential association rule mining to solve these problems from review data. Product reviews provide useful information for recommendations because product reviews include not only rating of the product but also various contents such as user experiences and emotional state. So, reviews imply user preference for the product. So, topic modeling is useful for explaining why items are recommended to users. In addition, sequential association rule mining is useful for identifying changes in user preferences. The proposed methodology is largely divided into two phases. The first phase is to create user profile based on topic modeling. After extracting topics from user reviews on products, user profile on topics is created. The second phase is to recommend products using sequential rules that appear in buying behaviors of users as time passes. The buying behaviors are derived from a change in the topic of each user. A collaborative filtering-based recommendation system was developed as a benchmark system, and we compared the performance of the proposed methodology with that of the collaborative filtering-based recommendation system using Amazon's review dataset. As evaluation metrics, accuracy, recall, precision, and F1 were used. For topic modeling, collapsed Gibbs sampling was conducted. And we extracted 15 topics. Looking at the main topics, topic 1, top 3, topic 4, topic 7, topic 9, topic 13, topic 14 are related to "comedy shows", "high-teen drama series", "crime investigation drama", "horror theme", "British drama", "medical drama", "science fiction drama", respectively. As a result of comparative analysis, the proposed methodology outperformed the collaborative filtering-based recommendation system. From the results, we found that the time just prior to the recommendation was very important for inferring changes in user preference. Therefore, the proposed methodology not only can secure the transparency of the recommender system but also can reflect the user's preferences that change over time. However, the proposed methodology has some limitations. The proposed methodology cannot recommend product elaborately if the number of products included in the topic is large. In addition, the number of sequential patterns is small because the number of topics is too small. Therefore, future research needs to consider these limitations.

• Asia pacific journal of information systems
• /
• v.24 no.4
• /
• pp.611-635
• /
• 2014

Information systems (IS) have become ubiquitous and changed every aspect of how people live their lives. While some IS have been successfully adopted and widely used, others have failed to be adopted and crowded out in spite of remarkable progress in technologies. Both the technology acceptance model (TAM) and the IS Success Model (ISSM), among many others, have contributed to explain the reasons of success as well as failure in IS adoption and usage. While the TAM suggests that intention to use and perceived usefulness lead to actual IS usage, the ISSM indicates that information quality, system quality, and service quality affect IS usage and user satisfaction. Upon literature review, however, we found a significant void in theoretical development and its applications that employ either of the two models, and we raise research questions. First of all, in spite of the causal relationship between intention to use and actual usage, in most previous studies, only intention to use was employed as a dependent variable without overt explaining its relationship with actual usage. Moreover, even in a few studies that employed actual IS usage as a dependent variable, the degree of actual usage was measured based on users' perceptual responses to survey questionnaires. However, the measurement of actual usage based on survey responses might not be 'actual' usage in a strict sense that responders' perception may be distorted due to their selective perceptions or stereotypes. By the same token, the degree of system quality that IS users perceive might not be 'real' quality as well. This study seeks to fill this void by measuring the variables of actual usage and system quality using 'fact' data such as system logs and specifications of users' information and communications technology (ICT) devices. More specifically, we propose an integrated research model that bring together the TAM and the ISSM. The integrated model is composed of both the variables that are to be measured using fact as well as survey data. By employing the integrated model, we expect to reveal the difference between real and perceived degree of system quality, and to investigate the relationship between the perception-based measure of intention to use and the fact-based measure of actual usage. Furthermore, we also aim to add empirical findings on the general research question: what factors influence actual IS usage and how? In order to address the research question and to examine the research model, we selected a mobile campus application (MCA). We collected both fact data and survey data. For fact data, we retrieved them from the system logs such information as menu usage counts, user's device performance, display size, and operating system revision version number. At the same time, we conducted a survey among university students who use an MCA, and collected 180 valid responses. A partial least square (PLS) method was employed to validate our research model. Among nine hypotheses developed, we found five were supported while four were not. In detail, the relationships between (1) perceived system quality and perceived usefulness, (2) perceived system quality and perceived intention to use, (3) perceived usefulness and perceived intention to use, (4) quality of device platform and actual IS usage, and (5) perceived intention to use and actual IS usage were found to be significant. In comparison, the relationships between (1) quality of device platform and perceived system quality, (2) quality of device platform and perceived usefulness, (3) quality of device platform and perceived intention to use, and (4) perceived system quality and actual IS usage were not significant. The results of the study reveal notable differences from those of previous studies. First, although perceived intention to use shows a positive effect on actual IS usage, its explanatory power is very weak ($R^2$=0.064). Second, fact-based system quality (quality of user's device platform) shows a direct impact on actual IS usage without the mediating role of intention to use. Lastly, the relationships between perceived system quality (perception-based system quality) and other constructs show completely different results from those between quality of device platform (fact-based system quality) and other constructs. In the post-hoc analysis, IS users' past behavior was additionally included in the research model to further investigate the cause of such a low explanatory power of actual IS usage. The results show that past IS usage has a strong positive effect on current IS usage while intention to use does not have, implying that IS usage has already become a habitual behavior. This study provides the following several implications. First, we verify that fact-based data (i.e., system logs of real usage records) are more likely to reflect IS users' actual usage than perception-based data. In addition, by identifying the direct impact of quality of device platform on actual IS usage (without any mediating roles of attitude or intention), this study triggers further research on other potential factors that may directly influence actual IS usage. Furthermore, the results of the study provide practical strategic implications that organizations equipped with high-quality systems may directly expect high level of system usage.

• Journal of the Korean Institute of Traditional Landscape Architecture
• /
• v.31 no.4
• /
• pp.95-112
• /
• 2013

Jangchungdan Park is now perceived as a mere park at the foot of Namsan mountain, but originally it was created to commemorate soldiers of Korean Empire on a site which name was Namsoyeong(南小營) during Joseon Dynasty. During the period of Japanese colonial rule, it was transformed into a park due to the rapidly changing circumstances, so the components expressing the validity of the colonial rule were introduced into the park. This paper examines the time sequential changes of Jangchungdan Park during the period of Japanese colonial rule, and the conclusions can be summarized as given below. Firstly, the park originally was a space to commemorate the soldiers who fought for the Korean Empire. It was built on formerly restricted area at the foot of Namsan Mountain in 1900, and it was arranged putting the ceremonial shrine Dansa (壇祠) as a central building and the annexes in the surroundings of it. The memorial ceremonies were held regularly in spring and autumn until 1909. Secondly, it became a city park for citizens of Gyeongseong-bu(the name of Seoul under the Japanese colonial rule). The authorities of Gyeongseong-bu reorganized Jangchungdan as a park in 1919, prohibited the performance of memorial ceremonies, and the existing buildings except the ceremonial shrine Dansa began to be used as park management facilities. Resting areas and amenities were supplemented for the usage of people from various backgrounds, and the large scale planting of cherry trees made the park a famous place to enjoy cherry-blossoms and other flowers in spring. Thirdly, it was reconstructed as a space to honor the influential personalities of Japanese colonial system. In 1932, Bankmun temple (博文寺) to commemorate Ito Hirobumi was constructed at a location that made it possible for a number of people to overlook Jangchungdan area. During that time, the buildings of traditional Joseon architecture were removed and reconstructed to serve as annexes to Bankmun temple. Due to the strategy to make Jangchungdan park a tourist attraction, Bankmun temple was included into the Gyeongseong sightseeing course, since the wide panorama of Jangchungdan Park and the whole city of Gyeongseong was opening from the temple. Various different components were introduced into Jangchungdan Park due to the rapidly changing circumstances; therefore the nature of the park was either altered or reproduced. Hopefully, the park rearrangement works will be executed paying respects to the memories of the past hereafter.

• The KIPS Transactions:PartB
• /
• v.13B no.5 s.108
• /
• pp.561-568
• /
• 2006

WPS(Wearable Personal Station) for next generation PC can define as a core terminal of 'Ubiquitous Computing' that include information processing and network function and overcome spatial limitation in acquisition of new information. As a way to acquire significant dynamic gesture data of user from haptic devices, traditional gesture recognizer based on desktop-PC using wire communication module has several restrictions such as conditionality on space, complexity between transmission mediums(cable elements), limitation of motion and incommodiousness on use. Accordingly, in this paper, in order to overcome these problems, we implement hand gesture recognition system using fuzzy algorithm and neural network for Post PC(the embedded-ubiquitous environment using blue-tooth module and WPS). Also, we propose most efficient and reasonable hand gesture recognition interface for Post PC through evaluation and analysis of performance about each gesture recognition system. The proposed gesture recognition system consists of three modules: 1) gesture input module that processes motion of dynamic hand to input data 2) Relational Database Management System(hereafter, RDBMS) module to segment significant gestures from input data and 3) 2 each different recognition modulo: fuzzy max-min and neural network recognition module to recognize significant gesture of continuous / dynamic gestures. Experimental result shows the average recognition rate of 98.8% in fuzzy min-nin module and 96.7% in neural network recognition module about significantly dynamic gestures.

• Journal of Korea Port Economic Association
• /
• v.34 no.4
• /
• pp.191-208
• /
• 2018

This paper focuses on the integration aspect of operators to determine an improvement strategy for the operating system to enhance competitiveness of Busan Port. This Study proposes the following alternatives: valuation standards for the integration of operators, the road map for the integration period, the scope and role setting of integrated operators' participation of Busan Port Authority(BPA), and the separation and linkage North Port and the New Port operators. First, the valuation standards for operator integration should be based on international standards. Additionally quantitative factors such as financial situation, business performance and participating companies' profitability, and the qualitative factors such as management ability, technology, and labor relations should be considered. Second, the timing of North Port's operator integration should be prioritized in the short term in conjunction with the commencement of its phase 2-4, 2-5, and 2-6. The integration of New Port operators should provide a road map for a relatively long-term perspective. Third, the participation of BPA' integrated operators should be considered in terms of publicity as a policy coordinator between terminals and by pursuing the profitability of entering into overseas business by fostering Korean global terminal operators. The scope and role of participation ensures that the experience and technology of the terminal operation business is maximized. Fourth, because physically intergrating the North Port' operator into a single corporate form is difficult, initially establishing a special purpose company to maximize the effect of the integrated operation is necessary. Then, the operators decided to convert to a holding company given the termination of the lease term contract with the State or BPA, and ultimately proposed a merger into a single corporation.

• Journal of vocational education research
• /
• v.36 no.2
• /
• pp.95-121
• /
• 2017

The vocational competency development training teacher must complete the training course for the training of vocational competency development training instructor and get the qualification of the vocational competency development training teacher from the Ministry of Employment & Labor with the criteria set by the Presidential Decree. Therefore, it can be said that H_university 's educational performance, which is the only vocational competency development training teacher in Korea and that plays a role of mass production in the labor market, has a great influence on vocational competency development training. The purpose of this study is to identify the problems through the analysis of actual condition of vocational competency development training education based on CIPP model, Furthermore, it was aimed to suggest improvement plan of qualification training education. In order to accomplish the purpose of the research, the present situation of the training course for the vocational competency development training teacher training students was grasped. And We conducted a survey to draw out the improvement plan and utilized the results of 173 copies. We conducted interviews by selecting eight subjects for in-depth analysis and Understand the details of the results of the surveys conducted. As a result of the study, positive responses were obtained from the educational objectives and educational resources in the context factors. On the other hand, there were negative opinions about the curriculum reflecting the learner and social needs. In the input factors, positive opinions were derived from the educational objectives and training requirements. However, there were many negative opinions about the achievement of the learner's educational goals. In addition, there were many negative opinions of online contents education. In the process factors, positive evaluation was high in class related part, learner attendance management, and institutional support. However, negative opinions were drawn on the comprehensive evaluation of qualification training period, and the learner's burden due to lack of learning period appeared to be the main reason. In the factor of calculation, Positive opinions were derived from the applicability of the business curriculum for training courses for training teachers who are in charge of education and training in industry occupations. However, there were negative opinions such as learning time, concentration of learning, and communication of instructors. Based on the results of the study, suggestions for improving the operation of vocational competency training teacher qualification training are as follows. First, it is necessary to flexibly manage the training schedule for the weekly training course for vocational competency development training teachers. Second, it is necessary to seek to improve the online education curriculum centered on consumers. Third, it is necessary to seek access to qualification training for local residents. Fourth, pre - education support for qualified applicants is required. Finally, follow-up care of qualified trainees is necessary.

• Journal of Intelligence and Information Systems
• /
• v.25 no.1
• /
• pp.139-161
• /
• 2019

The utilization of the e-commerce market has become a common life style in today. It has become important part to know where and how to make reasonable purchases of good quality products for customers. This change in purchase psychology tends to make it difficult for customers to make purchasing decisions in vast amounts of information. In this case, the recommendation system has the effect of reducing the cost of information retrieval and improving the satisfaction by analyzing the purchasing behavior of the customer. Amazon and Netflix are considered to be the well-known examples of sales marketing using the recommendation system. In the case of Amazon, 60% of the recommendation is made by purchasing goods, and 35% of the sales increase was achieved. Netflix, on the other hand, found that 75% of movie recommendations were made using services. This personalization technique is considered to be one of the key strategies for one-to-one marketing that can be useful in online markets where salespeople do not exist. Recommendation techniques that are mainly used in recommendation systems today include collaborative filtering and content-based filtering. Furthermore, hybrid techniques and association rules that use these techniques in combination are also being used in various fields. Of these, collaborative filtering recommendation techniques are the most popular today. Collaborative filtering is a method of recommending products preferred by neighbors who have similar preferences or purchasing behavior, based on the assumption that users who have exhibited similar tendencies in purchasing or evaluating products in the past will have a similar tendency to other products. However, most of the existed systems are recommended only within the same category of products such as books and movies. This is because the recommendation system estimates the purchase satisfaction about new item which have never been bought yet using customer's purchase rating points of a similar commodity based on the transaction data. In addition, there is a problem about the reliability of purchase ratings used in the recommendation system. Reliability of customer purchase ratings is causing serious problems. In particular, 'Compensatory Review' refers to the intentional manipulation of a customer purchase rating by a company intervention. In fact, Amazon has been hard-pressed for these "compassionate reviews" since 2016 and has worked hard to reduce false information and increase credibility. The survey showed that the average rating for products with 'Compensated Review' was higher than those without 'Compensation Review'. And it turns out that 'Compensatory Review' is about 12 times less likely to give the lowest rating, and about 4 times less likely to leave a critical opinion. As such, customer purchase ratings are full of various noises. This problem is directly related to the performance of recommendation systems aimed at maximizing profits by attracting highly satisfied customers in most e-commerce transactions. In this study, we propose the possibility of using new indicators that can objectively substitute existing customer 's purchase ratings by using RFM multi-dimensional analysis technique to solve a series of problems. RFM multi-dimensional analysis technique is the most widely used analytical method in customer relationship management marketing(CRM), and is a data analysis method for selecting customers who are likely to purchase goods. As a result of verifying the actual purchase history data using the relevant index, the accuracy was as high as about 55%. This is a result of recommending a total of 4,386 different types of products that have never been bought before, thus the verification result means relatively high accuracy and utilization value. And this study suggests the possibility of general recommendation system that can be applied to various offline product data. If additional data is acquired in the future, the accuracy of the proposed recommendation system can be improved.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.23 no.3
• /
• pp.149-155
• /
• 2021

Early warning systems for weather risk management in the agricultural sector have been developed to predict potential wind damage to crops. These systems take into account the daily maximum wind speed to determine the critical wind speed that causes fruit drops and provide the weather risk information to farmers. In an effort to increase the accuracy of wind risk predictions, an artificial neural network for binary classification was implemented. In the present study, the daily wind speed and other weather data, which were measured at weather stations at sites of interest in Jeollabuk-do and Jeollanam-do as well as Gyeongsangbuk- do and part of Gyeongsangnam- do provinces in 2019, were used for training the neural network. These weather stations include 210 synoptic and automated weather stations operated by the Korean Meteorological Administration (KMA). The wind speed data collected at the same locations between January 1 and December 12, 2020 were used to validate the neural network model. The data collected from December 13, 2020 to February 18, 2021 were used to evaluate the wind risk prediction performance before and after the use of the artificial neural network. The critical wind speed of damage risk was determined to be 11 m/s, which is the wind speed reported to cause fruit drops and damages. Furthermore, the maximum wind speeds were expressed using Weibull distribution probability density function for warning of wind damage. It was found that the accuracy of wind damage risk prediction was improved from 65.36% to 93.62% after re-classification using the artificial neural network. Nevertheless, the error rate also increased from 13.46% to 37.64%, as well. It is likely that the machine learning approach used in the present study would benefit case studies where no prediction by risk warning systems becomes a relatively serious issue.

• Journal of Bio-Environment Control
• /
• v.28 no.4
• /
• pp.293-301
• /
• 2019

The experiment was conducted to determine the performance of DME combustion gas when used as a fuel for DME burner for raising temperature and $CO_2$ concentration in greenhouse and also to examine its effects on chlorophyll content, and fresh and dry weight of lettuce and Chinese cabbage. DME-1 and DME-2 treatments consisted of average DME flow quantity in duct were $17.4m^3min^{-1}$ and $10.2m^3min^{-1}$ respectively to greenhouse-1 and greenhouse-2 and no DME gas was supplied to greenhouse-3 which was left as control (DME-3). DME supply times were $0.5hr\;day^{-1}$, $1hr\;day^{-1}$, $1:30hrs\;day^{-1}$ and $2hrs\;day^{-1}$ on week 1, 2, 3, and 4 respectively. Chlorophyll content and fresh and dry weight of lettuce and Chinese cabbage were measured for each treatment and analyzed through analysis of variance with a significance level of P<0.05. The result of the study showed that $CO_2$ concentration increased up to 265% and 174% and the level of temperature elevated $4.8^{\circ}C$ and $3.1^{\circ}C$ in greenhouse-1 and 2, respectively as compared to greenhouse-3 due to application of DME combustion gas. Although, the same crop management practices were provided in greenhouse-1, 2 and 3 at a same rate, the highest change (p<0.05) of chlorophyll content, fresh weight and dry weight were found from the DME-1 treatment, followed by DME-2. As a result, DME combustion gas that raised the level of temperature and $CO_2$ concentration in the greenhouse-1 and greenhouse-2, might have an effect on growth of lettuce and Chinese cabbage. At end of experiment, the highest fresh and dry weight of lettuce and Chinese cabbage were measured in greenhouse-1 and followed by greenhouse-2. Similarly chlorophyll content of greenhouse-1 and greenhouse-2 were more compared to greenhouse-3. In general, DME was not producing any harmful gas during its combustion period, therefore it can be used as an alternative to conventional fuel such as diesel and liquefied petroleum gas (LPG) for both heating and $CO_2$ supply in winter season. Moreover, endorsed quantify of DME combustion gas for a specified crop can be applied to greenhouse to improve the plant growth and enhance yield.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.22 no.1
• /
• pp.431-438
• /
• 2021

To prepare more stringent regulations for USCG Phase II ballast water management, this study investigated the staining efficiency of SYBR Green I(SGI) and SYBR Gold(SG) on the virus-like particle (VLP). A dye with high staining efficiency was applied to the treated water that was passed through the ballast water treatment system (BWTS). VLP staining was observed most clearly under the 100-fold and 200-fold dilution of the stock solution when the volume of filtered samples was 0.5 mL to 2 mL. The staining efficiency of SGI and SG did not show a significant difference. On the other hand, the green fluorescence of viruses in the sample stained with SGI was more pronounced than in the samples stained with SG (expressed yellow fluorescence), making it easier to observe. The abundance of VLP in the test water and control water treatments that did not pass through the two types of BWTS (electrolysis type, UV + electrolysis type) was approximately 109 - 1010 VLP 100 mL-1. In contrast, no stained VLP was observed in the treated water treatments. Moreover, SGI was confirmed to be effectively stained under various salinity conditions, including seawater, brackish water, and freshwater. Further verification tests and development of staining methods under various BWTS are required, but the SGI staining method is believed to be a good alternative to the VLP live/dead determination of the USCG Phase II type approval test.