• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.39-70
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• 2017

Data-drive analytics techniques have been recently applied to public surveys. Instead of simply gathering survey results or expert opinions to research the preference for a recently launched product, enterprises need a way to collect and analyze various types of online data and then accurately figure out customer preferences. In the main concept of existing data-based survey methods, the sentiment lexicon for a particular domain is first constructed by domain experts who usually judge the positive, neutral, or negative meanings of the frequently used words from the collected text documents. In order to research the preference for a particular product, the existing approach collects (1) review posts, which are related to the product, from several product review web sites; (2) extracts sentences (or phrases) in the collection after the pre-processing step such as stemming and removal of stop words is performed; (3) classifies the polarity (either positive or negative sense) of each sentence (or phrase) based on the sentiment lexicon; and (4) estimates the positive and negative ratios of the product by dividing the total numbers of the positive and negative sentences (or phrases) by the total number of the sentences (or phrases) in the collection. Furthermore, the existing approach automatically finds important sentences (or phrases) including the positive and negative meaning to/against the product. As a motivated example, given a product like Sonata made by Hyundai Motors, customers often want to see the summary note including what positive points are in the 'car design' aspect as well as what negative points are in thesame aspect. They also want to gain more useful information regarding other aspects such as 'car quality', 'car performance', and 'car service.' Such an information will enable customers to make good choice when they attempt to purchase brand-new vehicles. In addition, automobile makers will be able to figure out the preference and positive/negative points for new models on market. In the near future, the weak points of the models will be improved by the sentiment analysis. For this, the existing approach computes the sentiment score of each sentence (or phrase) and then selects top-k sentences (or phrases) with the highest positive and negative scores. However, the existing approach has several shortcomings and is limited to apply to real applications. The main disadvantages of the existing approach is as follows: (1) The main aspects (e.g., car design, quality, performance, and service) to a product (e.g., Hyundai Sonata) are not considered. Through the sentiment analysis without considering aspects, as a result, the summary note including the positive and negative ratios of the product and top-k sentences (or phrases) with the highest sentiment scores in the entire corpus is just reported to customers and car makers. This approach is not enough and main aspects of the target product need to be considered in the sentiment analysis. (2) In general, since the same word has different meanings across different domains, the sentiment lexicon which is proper to each domain needs to be constructed. The efficient way to construct the sentiment lexicon per domain is required because the sentiment lexicon construction is labor intensive and time consuming. To address the above problems, in this article, we propose a novel product reputation mining algorithm that (1) extracts topics hidden in review documents written by customers; (2) mines main aspects based on the extracted topics; (3) measures the positive and negative ratios of the product using the aspects; and (4) presents the digest in which a few important sentences with the positive and negative meanings are listed in each aspect. Unlike the existing approach, using hidden topics makes experts construct the sentimental lexicon easily and quickly. Furthermore, reinforcing topic semantics, we can improve the accuracy of the product reputation mining algorithms more largely than that of the existing approach. In the experiments, we collected large review documents to the domestic vehicles such as K5, SM5, and Avante; measured the positive and negative ratios of the three cars; showed top-k positive and negative summaries per aspect; and conducted statistical analysis. Our experimental results clearly show the effectiveness of the proposed method, compared with the existing method.

• Korean Journal of Construction Engineering and Management
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• v.19 no.6
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• pp.65-78
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• 2018

In As urban apartment are aging, the necessity of reconstruction or remodeling to extend the life of buildings is increasing. In such a case, a co-housing association is formed to implement decisions on reconstruction or remodeling projects. At this time, the most important thing for the co-housing association is the business feasibility based on the input of the construction cost.In the case of reconstruction, it is possible to estimate the construction cost by using the accumulated construction cost data, and then evaluate the feasibility using the construction cost. However, in case of remodeling, it is difficult to calculate the accurate construction cost because the number of accumulated construction cost data is small. In addition, non-specialist clients often require estimates of various design factors, often negatively impacting the accuracy of estimates and the duration of estimates. Therefore, in this study, proposed method to reflect the opinion of the owner who is a non-expert, as a design element, and a method of calculating the expected construction cost according to the design element, and constructed this system so that it can be easily used by the non-specialist owner. In order to clearly reflect the requirements of the non-specialist owner in the estimates, extracts the design elements from the existing remodeling cases, classify them, and suggest a plan for the client to choose. In order to reflect the design factors to the estimates, the existing apartment house remodeling cases were investigated and the design factors were extracted to have a large effect on the construction cost. Finally, developed system based on MS Excel so that the above contents can be easily used by a non-specialist client. In order to verify the accuracy of the proposed estimate in this study, verified the accuracy of 80% of the results by substituting the case of remodeling quotations and obtained a positive result from the questionnaire survey to examine the ease of use of the non-specialist customer. In this study, propose an estimate estimation method using four cases. If the remodeling cases are accumulated continuously, the expected effect of this study will be higher.

• Journal of Legislation Research
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• no.41
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• pp.337-366
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• 2011

In this article, I intend to analyze the definition of an employee under the Trade Union Act in Japan. Recently, the Supreme Court of Japan held that not only opera singer but also customer engineer is an employee under the Act. Conclusions are as follows:First, it is noteworthy that the Supreme Court reaffirmed the principle of all circumstances established by CBC case. The case focused on deciding that who is an employee under the Act. Notwithstanding this holding of the Supreme Court, district courts and courts of appeals, in deciding this kind of question, have emphasized especially on the side of a legal right and obligation on a contract between an employer and a potential employee. Therefore an independent contractor has not been generally recognized as an employee under the Act. However, even though he or she was, as an independent contractor in name, offering its work to his or her putative employer, the Supreme Court applied the principle of all circumstances to both cases and held in favor on the workers on April, in 2011. Second, the Supreme Court failed to make a general legal principle for deciding that who is an employee under the Act. According to the above holdings of the Supreme Court, nobody can anticipate wether he or she is an employee or not in a concrete case. Finally, the Supreme Court did not also make its opinion clearly about the relations between an employee of the Section 3 of the Act and an employee whom an employer employs under the Section 7(2) of the Act. In conclusion, it can be said that the Supreme Court has narrowly and strictly interpreted an employee of the Section 3. That is to say, only where an employee is recognized as an employee of the Section 7(2), the employee will be also an employee of the Section 3. In Japan, however, the majority interprets that an employee by the Section 3 should be distinguished from the employee whom an employer employs by the Section 7(2). Consequently, according to the majority opinions, unemployed persons, students and citizens will be also included in the definition of an employee by the Section 3.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.57-75
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• 2019

In this paper, we conducted a study focusing on the innovation direction of the documentary model on the Internet of Things industry, which is the most actively industrialized among the core technologies of the 4th Industrial Revolution. Policy, economic, social, and technical issues were derived using PEST analysis for global trend analysis. It also presented future prospects for the Internet of Things industry of ICT-related global research institutes such as Gartner and International Data Corporation. Global research institutes predicted that competition in network technologies will be an issue for industrial Internet (IIoST) and IoT (Internet of Things) based on infrastructure and platforms. As a result of the PEST analysis, developed countries are pushing policies to respond to the fourth industrial revolution through cooperation of private (business/ research institutes) led by the government. It was also in the process of expanding related R&D budgets and establishing related policies in South Korea. On the economic side, the growth tax of the related industries (based on the aggregate value of the market) and the performance of the entity were reviewed. The growth of industries related to the fourth industrial revolution in advanced countries overseas was found to be faster than other industries, while in Korea, the growth of the "technical hardware and equipment" and "communication service" sectors was relatively low among industries related to the fourth industrial revolution. On the social side, it is expected to cause enormous ripple effects across society, largely due to changes in technology and industrial structure, changes in employment structure, changes in job volume, etc. On the technical side, changes were taking place in each industry, representing the health and medical sectors and manufacturing sectors, which were rapidly changing as they merged with the technology of the Fourth Industrial Revolution. In this paper, various management methodologies for innovation of existing business model were reviewed to cope with rapidly changing industrial environment due to the fourth industrial revolution. In addition, four criteria were established to select a management model to cope with the new business environment: 'Applicability', 'Agility', 'Diversity' and 'Connectivity'. The expert survey results in an AHP analysis showing that Business Model Canvas is best suited for business model innovation methodology. The results showed very high importance, 42.5 percent in terms of "Applicability", 48.1 percent in terms of "Agility", 47.6 percent in terms of "diversity" and 42.9 percent in terms of "connectivity." Thus, it was selected as a model that could be diversely applied according to the industrial ecology and paradigm shift. Business Model Canvas is a relatively recent management strategy that identifies the value of a business model through a nine-block approach as a methodology for business model innovation. It identifies the value of a business model through nine block approaches and covers the four key areas of business: customer, order, infrastructure, and business feasibility analysis. In the paper, the expansion and application direction of the nine blocks were presented from the perspective of the IoT company (ICT). In conclusion, the discussion of which Business Model Canvas models will be applied in the ICT convergence industry is described. Based on the nine blocks, if appropriate applications are carried out to suit the characteristics of the target company, various applications are possible, such as integration and removal of five blocks, seven blocks and so on, and segmentation of blocks that fit the characteristics. Future research needs to develop customized business innovation methodologies for Internet of Things companies, or those that are performing Internet-based services. In addition, in this study, the Business Model Canvas model was derived from expert opinion as a useful tool for innovation. For the expansion and demonstration of the research, a study on the usability of presenting detailed implementation strategies, such as various model application cases and application models for actual companies, is needed.

• Journal of dental hygiene science
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• v.5 no.4
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• pp.211-220
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• 2005

The purpose of this study was to examine the job performance of dental coordinators and their perception of their job to lay the groundwork for utilizing dental personnels more efficiently. The subjects in this study were dental coordinators who worked at selected dental hospitals and clinics in Seoul, Gyeonggi province and Incheon. A survey was conducted to gather data from May 1 to August 8, 2005 and answer sheets from 108 respondents were analyzed. The findings of the study were as follows: 1. As for the length of service, 43.5 percent of the dental coordinators investigated had worked at dental institutes for five years or more, which was followed by less than two years(19.5%) and three years to less than five years(19.4%). Concerning the length of service as dental coordinators, 39.8 percent had served for less than two years, and 19.4 percent had worked for two years to less than three years and for five years or more respectively. Regarding the name of position, 38 percent were called team leaders, and 30.6 percent were called coordinators. As to duties, the largest group of them that stood at 30.6 percent were in charge of receiving, and in regard to department, the largest group, 57.4 percent, belonged to the treatment backup department. 2. Concerning education, the greatest number of them, 45.4 percent, had received education at private institutes, and 73.1 percent found it necessary for dental coordinators to take an authorized qualification test. 43.5 percent, the largest group, looked upon the central government as the best organization to authorize their qualifications and 70.8 percent believed that what they learned enabled them to perform their job successfully. As to the necessity of follow-up education as a means to improve job performance, 96.3 percent consented to it. As for the reason, 63.9 percent considered that necessary to enhance their own ability and 22.2 percent were in want of systematic education. Regarding educational expenses, 29.6 percent were subsidized by the dental institutes where they had worked and 25.9 percent had totally been responsible for that. Regarding a required course, medical service and marketing was most widely pointed out(66.7%), followed by theory and practice(65.7%) and introduction to dentistry(57.4%). As to what sort of education they wanted to receive more, dental service and marketing was selected the most, followed by practical health insurance(35.2%). 3. In regard to what type of job they performed as dental coordinators, 88.9 percent were in charge of appointment in the field of customer service, and 87.9 percent paid attention to having good manners as service providers in the area of self-management. In the field of hospital affairs, 81.3 percent were in charge of receiving. 4. As to their awareness of dental coordinator job, the largest group took pride in the job they performed ($3.99{\pm}0.76$), and the second largest group believed that dental coordinators made a great contribution to hospital management ($3.92{\pm}0.70$). The third largest group gave a great weight to their own job ($3.91{\pm}0.84$) in light of overall dental duties and the fourth largest group found themselves to get along with other employees regardless of position ($3.86{\pm}0.74$). The fifth largest group believed their job was of great use for promoting the oral health of patients ($3.76{\pm}0.75$), and the sixth largest group thought the future of dental coordinators was promising($3.74{\pm}0.86$). 5. In regard to their perception by age group, those who were older had a better opinion on every item of their job in general. Their age made a statistically significant difference to their view of the weight of dental coordinator job(P < 0.001) in light of overall dental duties, of being approved and trusted by managers(P < 0.01), of social awareness of dental coordinator, and of being understood and approved by other employees and dentists. Their pride in current job and their satisfaction with the name of their position were statistically significantly different according to their age as well. Besides, their age made a statistically significant difference to their opinion about whether or not there was an age limit to their occupation and about their contribution to hospital management (P < 0.05). 6. As for their perception by type of job, the dental hygienists were generally most satisfied with their job, followed by nursing aids and others. There was a statistically significant gap among their opinions about whether to make a job-related decision on their own(P < 0.001). the weight of their job in terms of overall dental duties, whether their job improved their ability, whether their job made a great contribution to enhancing the oral health of patients, whether their job was understood and approved by other employees(P < 0.01), social awareness of their job, whether they conflicted with other employees during job performance, and whether dental hospitals or clinics offered a self-development opportunity for them to take their ability to another level(P < 0.05). And their satisfaction with current pay was statistically significantly different as well.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.219-239
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• 2019

As the importance of providing customized services to individuals becomes important, researches on personalized recommendation systems are constantly being carried out. Collaborative filtering is one of the most popular systems in academia and industry. However, there exists limitation in a sense that recommendations were mostly based on quantitative information such as users' ratings, which made the accuracy be lowered. To solve these problems, many studies have been actively attempted to improve the performance of the recommendation system by using other information besides the quantitative information. Good examples are the usages of the sentiment analysis on customer review text data. Nevertheless, the existing research has not directly combined the results of the sentiment analysis and quantitative rating scores in the recommendation system. Therefore, this study aims to reflect the sentiments shown in the reviews into the rating scores. In other words, we propose a new algorithm that can directly convert the user 's own review into the empirically quantitative information and reflect it directly to the recommendation system. To do this, we needed to quantify users' reviews, which were originally qualitative information. In this study, sentiment score was calculated through sentiment analysis technique of text mining. The data was targeted for movie review. Based on the data, a domain specific sentiment dictionary is constructed for the movie reviews. Regression analysis was used as a method to construct sentiment dictionary. Each positive / negative dictionary was constructed using Lasso regression, Ridge regression, and ElasticNet methods. Based on this constructed sentiment dictionary, the accuracy was verified through confusion matrix. The accuracy of the Lasso based dictionary was 70%, the accuracy of the Ridge based dictionary was 79%, and that of the ElasticNet (${\alpha}=0.3$) was 83%. Therefore, in this study, the sentiment score of the review is calculated based on the dictionary of the ElasticNet method. It was combined with a rating to create a new rating. In this paper, we show that the collaborative filtering that reflects sentiment scores of user review is superior to the traditional method that only considers the existing rating. In order to show that the proposed algorithm is based on memory-based user collaboration filtering, item-based collaborative filtering and model based matrix factorization SVD, and SVD ++. Based on the above algorithm, the mean absolute error (MAE) and the root mean square error (RMSE) are calculated to evaluate the recommendation system with a score that combines sentiment scores with a system that only considers scores. When the evaluation index was MAE, it was improved by 0.059 for UBCF, 0.0862 for IBCF, 0.1012 for SVD and 0.188 for SVD ++. When the evaluation index is RMSE, UBCF is 0.0431, IBCF is 0.0882, SVD is 0.1103, and SVD ++ is 0.1756. As a result, it can be seen that the prediction performance of the evaluation point reflecting the sentiment score proposed in this paper is superior to that of the conventional evaluation method. In other words, in this paper, it is confirmed that the collaborative filtering that reflects the sentiment score of the user review shows superior accuracy as compared with the conventional type of collaborative filtering that only considers the quantitative score. We then attempted paired t-test validation to ensure that the proposed model was a better approach and concluded that the proposed model is better. In this study, to overcome limitations of previous researches that judge user's sentiment only by quantitative rating score, the review was numerically calculated and a user's opinion was more refined and considered into the recommendation system to improve the accuracy. The findings of this study have managerial implications to recommendation system developers who need to consider both quantitative information and qualitative information it is expect. The way of constructing the combined system in this paper might be directly used by the developers.