International Journal of Advanced Culture Technology
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v.8
no.4
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pp.263-270
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2020
The growth of the mobile app markets has made it popular among people who recommend relevant information about restaurants. The recommendation service app based on AI Chatbot is that it can efficiently manage time and finances by making it easy for restaurant consumers to easily access the information they want anytime, anywhere. Eating out consumers use smartphone applications for finding restaurants, making reservations, and getting reviews and how to use them. In addition, social attention has recently been focused on the research of AI chatbot. The Chatbot is combined with the mobile messenger platform and enabling various services due to the text-type interactive service. It also helps users to find the services and data that they need information tersely. Applying this to restaurant recommendation services will increase the reliability of the information in providing personal information. In this paper, an artificial intelligence chatbot-based smartphone restaurant recommendation app using personalization information is proposed. The recommendation service app utilizes personalization information such as gender, age, interests, occupation, search records, visit records, wish lists, reviews, and real-time location information. Users can get recommendations for restaurants that fir their purpose through chatting using AI chatbot. Furthermore, it is possible to check real-time information about restaurants, make reservations, and write reviews. The proposed app uses a collaborative filtering recommendation system, and users receive information on dining out using artificial intelligence chatbots. Through chatbots, users can receive customized services using personal information while minimizing time and space limitations.
Seo, Jiyu;Won, Jeongeun;Choi, Jeonghyeon;Kim, Sangdan
Journal of Korean Society on Water Environment
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v.37
no.3
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pp.204-216
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2021
It is important to understand the factors influencing the temporal and spatial variability of water quality in order to establish an effective customized management strategy for contaminated aquatic ecosystems. In this study, the spatial diversity of the 5-year (2015 - 2019) average total phosphorus (TP) concentration observed in 40 Total Maximum Daily Loads unit-basins in the Nakdong River watershed was analyzed using 50 predictive variables of watershed characteristics, climate characteristics, land use characteristics, and soil characteristics. Cross-correlation analysis, a two-stage exhaustive search approach, and Bayesian inference were applied to identify predictors that best matched the time-averaged TP. The predictors that were finally identified included watershed altitude, precipitation in fall, precipitation in winter, residential area, public facilities area, paddy field, soil available phosphate, soil magnesium, soil available silicic acid, and soil potassium. Among them, it was found that the most influential factors for the spatial difference of TP were watershed altitude in watershed characteristics, public facilities area in land use characteristics, and soil available silicic acid in soil characteristics. This means that artificial factors have a great influence on the spatial variability of TP. It is expected that the proposed statistical modeling approach can be applied to the identification of major factors affecting the spatial variability of the temporal average state of various water quality parameters.
Objectives: In the health care industry, the influence of online reviews is growing. As medical services are provided mainly by providers, those services have been managed by hospitals and clinics. However, direct promotions of medical services by providers are legally forbidden. Due to this reason, consumers, like patients and clients, search a lot of reviews on the Internet to get any information about hospitals, treatments, prices, etc. It can be determined that online reviews indicate the quality of hospitals, and that analysis should be done for sustainable hospital marketing. Method: Using a Python-based crawler, we collected reviews, written by real patients, who had experienced Korean medicine, about more than 14,000 reviews. To extract the most representative words, reviews were divided by positive and negative; after that reviews were pre-processed to get only nouns and adjectives to get TF(Term Frequency), DF(Document Frequency), and TF-IDF(Term Frequency - Inverse Document Frequency). Finally, to get some topics about reviews, aggregations of extracted words were analyzed by using LDA(Latent Dirichlet Allocation) methods. To avoid overlap, the number of topics is set by Davis visualization. Results and Conclusions: 6 and 3 topics extracted in each positive/negative review, analyzed by LDA Topic Model. The main factors, consisting of topics were 1) Response to patients and customers. 2) Customized treatment (consultation) and management. 3) Hospital/Clinic's environments.
Journal of the Korea Society of Computer and Information
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v.14
no.4
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pp.179-187
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2009
Most real world systems contain a series of dynamic and complex phenomena. One of common methods to understand these systems is to build a model and analyze the behavior of them. A two-step methodology comprised of clustering and then model creation is proposed for the analysis on time series data. An interface is designed for CRM(Customer Relationship Management) that provides user with 1:1 customized information using system modeling. It was confirmed from experiments that better clustering would be derived from model based approach than similarity based one. Clustering is followed by model creation over the clustered groups, by which future direction of time series data movement could be predicted. The effectiveness of the method was validated by checking how similarly predicted values from the models move together with real data such as stock prices.
Journal of Wellbeing Management and Applied Psychology
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v.6
no.2
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pp.15-26
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2023
Purpose: It is necessary to prepare more groundbreaking measures to prevent recurrence in order to reduce the number of industrial accidents in Korea that occur steadily. In particular, since workers with disabilities are much more vulnerable to disaster safety than non-disabled workers, there is a great need to build a customized safety environment system suitable for the characteristics of the work in which workers with disabilities work and to promote management efficiency. Research design, data and methodology: Based on the analysis of the actual status of safety and health management of workplaces for the disabled, such as small, medium-sized and major businesses in Korea, an app was designed and developed to improve safety and health management efficiency of workplaces for the disabled. First, it was designed so that managers of workplaces with disabilities can understand at a glance key legal information that managers need to know and it was improved to suit the eye level of disabled workers so that they could self-evaluate the risk of their work by applying the risk assessment model for workplaces with disabilities. In addition, a mobile education environment was created in which safety and health education contents suitable for the characteristics of disabled workers can be learned by themselves. Results: When this app is applied to domestic workplaces, it is possible to check the exact contents of occupational safety and health education and easily search and check various legal information anytime, anywhere, allowing managers and disabled workers to quickly and efficiently manage various safety information. Conclusions: In addition, the establishment of a mobile safety and health management system that can quickly identify and clearly respond to various legal standards and risks of workplaces with disabilities can be expected to help prevent industrial accidents at workplaces with disabilities in Korea.
This study aims to help companies with efficient investment and marketing strategies by empirically verifying the impact on satisfaction and purchase intention for artificial intelligence-based digital technology supported shopping assistants introduced in e-commerce. Frequency, factor, SEM, and multiple group analysises were conducted using SPSS 26.0 and Amos 26.0. As a result, first, motivated consumer innovativeness elements of AI shopping assistant were derived into a total of four categories: functional, hedonic, rational, and reliable. Second, in the order of hedonic and rational, satisfaction with the AI shopping assistant was significantly affected, and in the order of rational and functional, purchase intention was significantly affected. The satisfaction with the AI shopping assistant did not affect the purchase intention. Third, in the case of hedonic, the AI-preferred group had a more significant effect on satisfaction than the human-preferred group, and in the case of rational, there was no difference by group in purchase intention. Thus, it was found that consumers prefer AI shopping helpers for e-commerce because they can shop reasonably and are functionally convenient. Therefore, when introducing AI shopping assistants, it is essential to include content that can compare and analyze fundamental information, such as product prices, as well as search functions and payment system compatibility that facilitate shopping.
Recently, the "Smart Consumer" has been emerging. He or she is increasingly inclined to search for and purchase products by taking into account personal judgment or expert reviews rather than by relying on information delivered through manufacturers' advertising. This is especially true when purchasing cosmetics. Because cosmetics act directly on the skin, consumers respond seriously to dangerous chemical elements they contain or to skin problems they may cause. Above all, cosmetics should fit well with the purchaser's skin type. In addition, changes in global cosmetics consumer trends make it necessary to study this field. The desire to find one's own individualized cosmetics is being revealed to consumers around the world and is known as "Finding the Holy Grail." Many consumers show a deep interest in customized cosmetics with the cultural boom known as "K-Beauty" (an aspect of "Han-Ryu"), the growth of personal grooming, and the emergence of "self-culture" that includes "self-beauty" and "self-interior." These trends have led to the explosive popularity of cosmetics made in Korea in the Chinese and Southeast Asian markets. In order to meet the customized cosmetics needs of consumers, cosmetics manufacturers and related companies are responding by concentrating on delivering premium services through the convergence of ICT(Information, Communication and Technology). Despite the evolution of companies' responses regarding market trends toward customized cosmetics, there is no "Intelligent Data Platform" that deals holistically with consumers' skin condition experience and thus attaches emotions to products and services. To find the Holy Grail of customized cosmetics, it is important to acquire and analyze consumer data on what they want in order to address their experiences and emotions. The emotions consumers are addressing when purchasing cosmetics varies by their age, sex, skin type, and specific skin issues and influences what price is considered reasonable. Therefore, it is necessary to classify emotions regarding cosmetics by individual consumer. Because of its importance, consumer emotion analysis has been used for both services and products. Given the trends identified above, we judge that consumer emotion analysis can be used in our study. Therefore, we collected and indexed data on consumers' emotions regarding their cosmetics experiences focusing on consumers' language. We crawled the cosmetics emotion data from SNS (blog and Twitter) according to sales ranking ($1^{st}$ to $99^{th}$), focusing on the ample/serum category. A total of 357 emotional adjectives were collected, and we combined and abstracted similar or duplicate emotional adjectives. We conducted a "Consumer Sentiment Journey" workshop to build a "Consumer Sentiment Dictionary," and this resulted in a total of 76 emotional adjectives regarding cosmetics consumer experience. Using these 76 emotional adjectives, we performed clustering with the Self-Organizing Map (SOM) method. As a result of the analysis, we derived eight final clusters of cosmetics consumer sentiments. Using the vector values of each node for each cluster, the characteristics of each cluster were derived based on the top ten most frequently appearing consumer sentiments. Different characteristics were found in consumer sentiments in each cluster. We also developed a cosmetics experience pattern map. The study results confirmed that recommendation and classification systems that consider consumer emotions and sentiments are needed because each consumer differs in what he or she pursues and prefers. Furthermore, this study reaffirms that the application of emotion and sentiment analysis can be extended to various fields other than cosmetics, and it implies that consumer insights can be derived using these methods. They can be used not only to build a specialized sentiment dictionary using scientific processes and "Design Thinking Methodology," but we also expect that these methods can help us to understand consumers' psychological reactions and cognitive behaviors. If this study is further developed, we believe that it will be able to provide solutions based on consumer experience, and therefore that it can be developed as an aspect of marketing intelligence.
Outcome of election depends on which candidate of politics uses more original and creative idea for Ads and PR of election in election campaign strategy of political campaign. Especially, since political Ads and PR are the ways of capturing voters' sensitivities with one line of copy(slogan) and one image, Ads and PR are very important. This research analyzes unique and creative trend of political campaigns which are used in each unit election which is held four times(2010. 6 2 local election, 2011. 10 26 by-election, 2012. 4 11 general election, 2012. 12 19 presidential election) during 2010~2012. For analysis, search analysis of text and image used in video, internet, booklet type of Ads and PR material for election, and election campaign. Video is used in election campaign during election period. Unique and creative political campaign is customized micro-marketing election strategy trend which tries to fit for tendency of backing including gender, age group, social atmosphere, etc. This research excludes the degree of success of this election strategy from subject of analysis.
The major objective of this research is to suggest the proactive strategy and management of public R&D for the active transfer of technology based on the influential factor analysis of technology transfer. This study identified influential factors which make the greatest impact on the success of public technology transfer and commercialization through three points of view-technology supplier's view, technology adopter's view and view of commercialization-which contribute to successful technology transfer and commercialization. The core influential variables for blocking technology transfer are identified such as additional technological development, search for technology adopter followed by mass production technology and testing of confidence. Technology adopter is to create new markets or expand existing markets through the superiority (innovation) of licensing technology, increasing the internal innovation capabilities and maximizing the impacts of technology. This research suggests two effective strategies for improving technology transfer such as technology planning and marketing in the view of technology license. The strategy of technology planning should be established and executed to meet both technology trends and adopter's needs. And strong patents should be secured in terms of licensing of technology. Also the technological performance should be evaluated at mid-term appraisal, confirming the needs of adopter and competitive advantage of technology and patent. In addition to this, the customized technology marketing strategy for different fields of applications is also required in order to improve the likelihood of technology transfer. If the performance of R&D organization could be evaluated by global technological competitiveness and spillover effects of commercialization rather than quantitative output, the flow of technology transfer and commercialization would be accelerated.
Journal of the Korean Society for Library and Information Science
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v.43
no.2
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pp.5-28
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2009
The purpose of this study is to investigate the use of the electronic information resources of humanities scholars in Korea and propose the planning of academic library and information services to serve their needs. To collect data, a postal survey was conducted during the period of November 2007 through January 2008. Out of 799 humanities scholars sampled from 25 universities, 132 responded with a completion rate of 16%. The major findings of this study are as follows: Firstly, the majority of humanities scholars distribute their time equally between research and education, and conduct independent research. Secondly, they use, to a certain degree, electronic information resources largely in text format, and depend upon the electronic collection of their academic libraries. Thirdly, with the exception of a couple of sources of electronic journal resources, the electronic resources that these humanities scholars regularly use vary so widely that none could be considered to be a common resource. Fourthly, they value the convenience of accessing and using electronic resources, but worry about the quality and scope of the contents. It is suggested that academic libraries (1) become the gateway for the electronic information that is available both inside and outside the library, (2) provide integrated search feature for and a 'single sign on' access to electronic resources, and (3) plan customized user education for specific subject fields in the humanities.
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