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

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.3
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• pp.193-211
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• 2021

Recently, interest in Korean Wave craze and K-beauty, led by K-pop, is increasing. In addition, the popularity and influence of the domestic beauty service industry has increased, and the economic and cultural ripple effects have been continuously expanding. The need to professional manpower training in response to the demand for manpower due to the growing development of domestic beauty services is emphasized, and the number of trainees who are actual consumers of beauty academy is increasing. Therefore, the purpose of our study is to examine the importance of quality factors of educational services to achieve educational purposes in the educational services provided by the Beauty Academy and the relationship between relationship commitment and educational service performance. Furthermore, it is to draw the importance of administrative support services, educational programs as well as educational service provision activities. However, the research for professional manpower training according to the provision of beauty services is insufficient compared to the development speed of the beauty industry. Therefore, at the present time when beauty service education is emphasized, our study will examine the relationship between relationship commitment and educational service performance based on the quality of education service by the students of domestic beauty academy. The measurement variables set for our study are program, instructor quality, tuition, external service, service fairness, relationship commitment, trust level, and educational service performance. The variables were analyzed and derived through the survey, and the following contents were derived from the empirical analysis. First, the quality of education service provided by the beauty academy, such as program, external service, service fairness, relationship commitment and trust level, had a significant effect on relationship commitment. Educational services provided by the institute, such as the systematicity and diversity of educational programs, enabled students to have a uniform relationship commitment. The quality of education service itself is to learn the expertise necessary for providing beauty service from the standpoint of the students and play an organic role in the relationship with the institute. Second, the moderating effect of trust level between academies and students was significant in the quality of education service and the relationship commitment. This means that students will feel higher level of service quality through the practical trust relationship of the students about the educational services provided by the institute. Based on the results of the empirical analysis, the implications of our study are to find ways to improve the students' ability and satisfaction represented by the results of educational services. This is because the quality of education services provided by the institute called Beauty Academy will have a great impact on the career choice of educational facilities and students. The characteristics of consistency, convenience, and knowledge orientation of education itself should be considered comprehensively, and a strong market position should be established through image formation through external service factors, which are external environments of academies.Furthermore, in terms of presenting differentiated strategies with competitors, the educational service quality factors play a significant role in the commitment to the relationship with the students, so the role of relationship marketing will be important for the psychological stability experienced by the students by grasping the demand accompanying the behavior of the students in advance.