• Title/Summary/Keyword: Academic Performance

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A Study about Impact of Mindfulness on Perceived Factors of Information Technology Acceptance (마음챙김이 정보기술 수용의 인지적 요인에 미치는 영향 연구)

  • Hyun Mo Kim;Ying Ying Pang;Joo Seok Park
    • Information Systems Review
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    • v.21 no.1
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    • pp.1-22
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    • 2019
  • Mindfulness is the process of actively noticing new things. Today, companies have introduced and run mindfulness programs because the mindfulness has possible applications of productivity and innovation in corporation. However, role of mindfulness has not been clearly investigated in behavior research of Information System. The purpose of this study is to confirm the effects of mindfulness on technology acceptance process. Based on UTAUT Model, we examined how mindfulness in technology acceptance process moderate antecedent factors of acceptance intentions and use behavior. For empirical research, we conducted a survey on acceptance of smart watch of internet of things for employees of companies applying the mindfulness programs. then, we analyzed survey sample in empirical methodologies. Based on the empirical analysis, cognizance of alternative technologies in mindfulness factors increased the impact of performance expectancy on acceptance intention. Novelty seeking in mindfulness factors increased the impact of effort expectancy on acceptance intention. Awareness of local context in mindfulness factors decreased the impact of social influence on acceptance intention. engagement with technology in mindfulness factors increased the impact of facilitating conditions on use behavior. This study suggests academic implications and practical implications based on the results of the research. The implications will help to support and extend the theory of technology acceptance model while providing practical insights for IT acceptance by suggesting ways to utilize mindfulness in corporation.

The impact of sports rehabilitation education on career and employment will through psychological resistance (스포츠 재활 교육이 심리적 반발을 통해 진로 및 취업 의지에 미치는 영향)

  • Song Ki-Jae
    • The Journal of the Convergence on Culture Technology
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    • v.10 no.2
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    • pp.187-199
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    • 2024
  • Due to the educational ecosystem in South Korea, there is a significant need to explore a new balance for students who pursue sports rehabilitation education based on their academic performance, in order to help them adapt to their majors, find career paths, and foster motivation for employment. There is a lack of related research in this crucial phase. The purpose of this study is to ascertain the impact of sports rehabilitation education on career aspirations and employment motivation through psychological reactions. The research methodology involved conducting an online survey from December 11th to December 28th, 2023, targeting university students undergoing sports rehabilitation education, with a final collection of 212 survey responses used for analysis. The research findings indicate: firstly, that the knowledge of sports rehabilitation educators has a positive influence on voluntary psychology. Secondly, the competence of sports rehabilitation educators has a positive impact on voluntary psychology. Thirdly, the attitude of sports rehabilitation educators negatively affects involuntary psychology. Fourthly, voluntary psychology positively influences career aspirations. Finally, voluntary psychology positively influences employment motivation, while conversely, involuntary psychology negatively affects employment motivation. These research results are expected to contribute to the development of sports rehabilitation education that influences career paths and employment motivation through psychological reactions.

2023 Survey on User Experience of Artificial Intelligence Software in Radiology by the Korean Society of Radiology

  • Eui Jin Hwang;Ji Eun Park;Kyoung Doo Song;Dong Hyun Yang;Kyung Won Kim;June-Goo Lee;Jung Hyun Yoon;Kyunghwa Han;Dong Hyun Kim;Hwiyoung Kim;Chang Min Park;Radiology Imaging Network of Korea for Clinical Research (RINK-CR)
    • Korean Journal of Radiology
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    • v.25 no.7
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    • pp.613-622
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    • 2024
  • Objective: In Korea, radiology has been positioned towards the early adoption of artificial intelligence-based software as medical devices (AI-SaMDs); however, little is known about the current usage, implementation, and future needs of AI-SaMDs. We surveyed the current trends and expectations for AI-SaMDs among members of the Korean Society of Radiology (KSR). Materials and Methods: An anonymous and voluntary online survey was open to all KSR members between April 17 and May 15, 2023. The survey was focused on the experiences of using AI-SaMDs, patterns of usage, levels of satisfaction, and expectations regarding the use of AI-SaMDs, including the roles of the industry, government, and KSR regarding the clinical use of AI-SaMDs. Results: Among the 370 respondents (response rate: 7.7% [370/4792]; 340 board-certified radiologists; 210 from academic institutions), 60.3% (223/370) had experience using AI-SaMDs. The two most common use-case of AI-SaMDs among the respondents were lesion detection (82.1%, 183/223), lesion diagnosis/classification (55.2%, 123/223), with the target imaging modalities being plain radiography (62.3%, 139/223), CT (42.6%, 95/223), mammography (29.1%, 65/223), and MRI (28.7%, 64/223). Most users were satisfied with AI-SaMDs (67.6% [115/170, for improvement of patient management] to 85.1% [189/222, for performance]). Regarding the expansion of clinical applications, most respondents expressed a preference for AI-SaMDs to assist in detection/diagnosis (77.0%, 285/370) and to perform automated measurement/quantification (63.5%, 235/370). Most respondents indicated that future development of AI-SaMDs should focus on improving practice efficiency (81.9%, 303/370) and quality (71.4%, 264/370). Overall, 91.9% of the respondents (340/370) agreed that there is a need for education or guidelines driven by the KSR regarding the use of AI-SaMDs. Conclusion: The penetration rate of AI-SaMDs in clinical practice and the corresponding satisfaction levels were high among members of the KSR. Most AI-SaMDs have been used for lesion detection, diagnosis, and classification. Most respondents requested KSR-driven education or guidelines on the use of AI-SaMDs.

Difficulties Experienced by Leading Korean Scientists and Implications for Science Education (한국의 선도적 과학자가 경험한 어려움과 과학교육에의 시사점)

  • Yeon Su Jung;Jung Bog Kim
    • Journal of The Korean Association For Science Education
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    • v.44 no.4
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    • pp.343-360
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    • 2024
  • The purpose of this study is to analyze the difficulties with scientific research faced by leading Korean scientists and suggest implications for science education. Data were collected through semi-structured interviews with 13 leading Korean scientists and were qualitatively analyzed using constructivist grounded theory. The results of the study showed that the leading scientists encountered 11 subcategories of difficulties, which were grouped into three main categories: uncharted territory, unexpected situations, and a lack of resources in domestic research environments. 'Uncharted territory' comprised anxiety due to uncertainty about research performance, insufficient knowledge accumulation in the field of research, and the burden of maintaining research influence as an academic leader. 'Unexpected situations' included encountering new phenomena that cannot be explained by existing theories, an inability to utilize research results, and repeated failures. 'A lack of resources in domestic research environments' included inadequate research funding support systems, a shortage of expert networks, limitations on employment and career opportunities for students, poor research equipment, and insufficient support policies for retired researchers. This study provides science educators with implications for the direction of science education and R&E. For students, it can serve as career education material, their attitudes towards science and their understanding of its nature. Lastly, the study may contribute to finding ways to improve scientific research policies and to developing a culture that fosters expertise in science.

Effects of Customers' Relationship Networks on Organizational Performance: Focusing on Facebook Fan Page (고객 간 관계 네트워크가 조직성과에 미치는 영향: 페이스북 기업 팬페이지를 중심으로)

  • Jeon, Su-Hyeon;Kwahk, Kee-Young
    • Journal of Intelligence and Information Systems
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    • v.22 no.2
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    • pp.57-79
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    • 2016
  • It is a rising trend that the number of users using one of the social media channels, the Social Network Service, so called the SNS, is getting increased. As per to this social trend, more companies have interest in this networking platform and start to invest their funds in it. It has received much attention as a tool spreading and expanding the message that a company wants to deliver to its customers and has been recognized as an important channel in terms of the relationship marketing with them. The environment of media that is radically changing these days makes possible for companies to approach their customers in various ways. Particularly, the social network service, which has been developed rapidly, provides the environment that customers can freely talk about products. For companies, it also works as a channel that gives customized information to customers. To succeed in the online environment, companies need to not only build the relationship between companies and customers but focus on the relationship between customers as well. In response to the online environment with the continuous development of technology, companies have tirelessly made the novel marketing strategy. Especially, as the one-to-one marketing to customers become available, it is more important for companies to maintain the relationship marketing with their customers. Among many SNS, Facebook, which many companies use as a communication channel, provides a fan page service for each company that supports its business. Facebook fan page is the platform that the event, information and announcement can be shared with customers using texts, videos, and pictures. Companies open their own fan pages in order to inform their companies and businesses. Such page functions as the websites of companies and has a characteristic of their brand communities such as blogs as well. As Facebook has become the major communication medium with customers, companies recognize its importance as the effective marketing channel, but they still need to investigate their business performances by using Facebook. Although there are infinite potentials in Facebook fan page that even has a function as a community between users, which other platforms do not, it is incomplete to regard companies' Facebook fan pages as communities and analyze them. In this study, it explores the relationship among customers through the network of the Facebook fan page users. The previous studies on a company's Facebook fan page were focused on finding out the effective operational direction by analyzing the use state of the company. However, in this study, it draws out the structural variable of the network, which customer committment can be measured by applying the social network analysis methodology and investigates the influence of the structural characteristics of network on the business performance of companies in an empirical way. Through each company's Facebook fan page, the network of users who engaged in the communication with each company is exploited and it is the one-mode undirected binary network that respectively regards users and the relationship of them in terms of their marketing activities as the node and link. In this network, it draws out the structural variable of network that can explain the customer commitment, who pressed "like," made comments and shared the Facebook marketing message, of each company by calculating density, global clustering coefficient, mean geodesic distance, diameter. By exploiting companies' historical performance such as net income and Tobin's Q indicator as the result variables, this study investigates influence on companies' business performances. For this purpose, it collects the network data on the subjects of 54 companies among KOSPI-listed companies, which have posted more than 100 articles on their Facebook fan pages during the data collection period. Then it draws out the network indicator of each company. The indicator related to companies' performances is calculated, based on the posted value on DART website of the Financial Supervisory Service. From the academic perspective, this study suggests a new approach through the social network analysis methodology to researchers who attempt to study the business-purpose utilization of the social media channel. From the practical perspective, this study proposes the more substantive marketing performance measurements to companies performing marketing activities through the social media and it is expected that it will bring a foundation of establishing smart business strategies by using the network indicators.

A Study on the Buyer's Decision Making Models for Introducing Intelligent Online Handmade Services (지능형 온라인 핸드메이드 서비스 도입을 위한 구매자 의사결정모형에 관한 연구)

  • Park, Jong-Won;Yang, Sung-Byung
    • Journal of Intelligence and Information Systems
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    • v.22 no.1
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    • pp.119-138
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    • 2016
  • Since the Industrial Revolution, which made the mass production and mass distribution of standardized goods possible, machine-made (manufactured) products have accounted for the majority of the market. However, in recent years, the phenomenon of purchasing even more expensive handmade products has become a noticeable trend as consumers have started to acknowledge the value of handmade products, such as the craftsman's commitment, belief in their quality and scarcity, and the sense of self-esteem from having them,. Consumer interest in these handmade products has shown explosive growth and has been coupled with the recent development of three-dimensional (3D) printing technologies. Etsy.com is the world's largest online handmade platform. It is no different from any other online platform; it provides an online market where buyers and sellers virtually meet to share information and transact business. However, Etsy.com is different in that shops within this platform only deal with handmade products in a variety of categories, ranging from jewelry to toys. Since its establishment in 2005, despite being limited to handmade products, Etsy.com has enjoyed rapid growth in membership, transaction volume, and revenue. Most recently in April 2015, it raised funds through an initial public offering (IPO) of more than 1.8 billion USD, which demonstrates the huge potential of online handmade platforms. After the success of Etsy.com, various types of online handmade platforms such as Handmade at Amazon, ArtFire, DaWanda, and Craft is ART have emerged and are now competing with each other, at the same time, which has increased the size of the market. According to Deloitte's 2015 holiday survey on which types of gifts the respondents plan to buy during the holiday season, about 16% of U.S. consumers chose "homemade or craft items (e.g., Etsy purchase)," which was the same rate as those for the computer game and shoes categories. This indicates that consumer interests in online handmade platforms will continue to rise in the future. However, this high interest in the market for handmade products and their platforms has not yet led to academic research. Most extant studies have only focused on machine-made products and intelligent services for them. This indicates a lack of studies on handmade products and their intelligent services on virtual platforms. Therefore, this study used signaling theory and prior research on the effects of sellers' characteristics on their performance (e.g., total sales and price premiums) in the buyer-seller relationship to identify the key influencing e-Image factors (e.g., reputation, size, information sharing, and length of relationship). Then, their impacts on the performance of shops within the online handmade platform were empirically examined; the dataset was collected from Etsy.com through the application of web harvesting technology. The results from the structural equation modeling revealed that the reputation, size, and information sharing have significant effects on the total sales, while the reputation and length of relationship influence price premiums. This study extended the online platform research into online handmade platform research by identifying key influencing e-Image factors on within-platform shop's total sales and price premiums based on signaling theory and then performed a statistical investigation. These findings are expected to be a stepping stone for future studies on intelligent online handmade services as well as handmade products themselves. Furthermore, the findings of the study provide online handmade platform operators with practical guidelines on how to implement intelligent online handmade services. They should also help shop managers build their marketing strategies in a more specific and effective manner by suggesting key influencing e-Image factors. The results of this study should contribute to the vitalization of intelligent online handmade services by providing clues on how to maximize within-platform shops' total sales and price premiums.

Enhancing Predictive Accuracy of Collaborative Filtering Algorithms using the Network Analysis of Trust Relationship among Users (사용자 간 신뢰관계 네트워크 분석을 활용한 협업 필터링 알고리즘의 예측 정확도 개선)

  • Choi, Seulbi;Kwahk, Kee-Young;Ahn, Hyunchul
    • Journal of Intelligence and Information Systems
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    • v.22 no.3
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    • pp.113-127
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    • 2016
  • Among the techniques for recommendation, collaborative filtering (CF) is commonly recognized to be the most effective for implementing recommender systems. Until now, CF has been popularly studied and adopted in both academic and real-world applications. The basic idea of CF is to create recommendation results by finding correlations between users of a recommendation system. CF system compares users based on how similar they are, and recommend products to users by using other like-minded people's results of evaluation for each product. Thus, it is very important to compute evaluation similarities among users in CF because the recommendation quality depends on it. Typical CF uses user's explicit numeric ratings of items (i.e. quantitative information) when computing the similarities among users in CF. In other words, user's numeric ratings have been a sole source of user preference information in traditional CF. However, user ratings are unable to fully reflect user's actual preferences from time to time. According to several studies, users may more actively accommodate recommendation of reliable others when purchasing goods. Thus, trust relationship can be regarded as the informative source for identifying user's preference with accuracy. Under this background, we propose a new hybrid recommender system that fuses CF and social network analysis (SNA). The proposed system adopts the recommendation algorithm that additionally reflect the result analyzed by SNA. In detail, our proposed system is based on conventional memory-based CF, but it is designed to use both user's numeric ratings and trust relationship information between users when calculating user similarities. For this, our system creates and uses not only user-item rating matrix, but also user-to-user trust network. As the methods for calculating user similarity between users, we proposed two alternatives - one is algorithm calculating the degree of similarity between users by utilizing in-degree and out-degree centrality, which are the indices representing the central location in the social network. We named these approaches as 'Trust CF - All' and 'Trust CF - Conditional'. The other alternative is the algorithm reflecting a neighbor's score higher when a target user trusts the neighbor directly or indirectly. The direct or indirect trust relationship can be identified by searching trust network of users. In this study, we call this approach 'Trust CF - Search'. To validate the applicability of the proposed system, we used experimental data provided by LibRec that crawled from the entire FilmTrust website. It consists of ratings of movies and trust relationship network indicating who to trust between users. The experimental system was implemented using Microsoft Visual Basic for Applications (VBA) and UCINET 6. To examine the effectiveness of the proposed system, we compared the performance of our proposed method with one of conventional CF system. The performances of recommender system were evaluated by using average MAE (mean absolute error). The analysis results confirmed that in case of applying without conditions the in-degree centrality index of trusted network of users(i.e. Trust CF - All), the accuracy (MAE = 0.565134) was lower than conventional CF (MAE = 0.564966). And, in case of applying the in-degree centrality index only to the users with the out-degree centrality above a certain threshold value(i.e. Trust CF - Conditional), the proposed system improved the accuracy a little (MAE = 0.564909) compared to traditional CF. However, the algorithm searching based on the trusted network of users (i.e. Trust CF - Search) was found to show the best performance (MAE = 0.564846). And the result from paired samples t-test presented that Trust CF - Search outperformed conventional CF with 10% statistical significance level. Our study sheds a light on the application of user's trust relationship network information for facilitating electronic commerce by recommending proper items to users.

Development of a Window Program for Searching CpG Island (CpG Island 검색용 윈도우 프로그램 개발)

  • Kim, Ki-Bong
    • Journal of Life Science
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    • v.18 no.8
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    • pp.1132-1139
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    • 2008
  • A CpG island is a short stretch of DNA in which the frequency of the CG dinucleotide is higher than other regions. CpG islands are present in the promoters and exonic regions of approximately $30{\sim}60$% of mammalian genes so they are useful markers for genes in organisms containing 5-methylcytosine in their genomes. Recent evidence supports the notion that the hypermethylation of CpG island, by silencing tumor suppressor genes, plays a major causal role in cancer, which has been described in almost every tumor types. In this respect, CpG island search by computational methods is very helpful for cancer research and computational promoter and gene predictions. I therefore developed a window program (called CpGi) on the basis of CpG island criteria defined by D. Takai and P. A. Jones. The program 'CpGi' was implemented in Visual C++ 6.0 and can determine the locations of CpG islands using diverse parameters (%GC, Obs (CpG)/Exp (CpG), window size, step size, gap value, # of CpG, length) specified by user. The analysis result of CpGi provides a graphical map of CpG islands and G+C% plot, where more detailed information on CpG island can be obtained through pop-up window. Two human contigs, i.e. AP00524 (from chromosome 22) and NT_029490.3 (from chromosome 21), were used to compare the performance of CpGi and two other public programs for the accuracy of search results. The two other programs used in the performance comparison are Emboss-CpGPlot and CpG Island Searcher that are web-based public CpG island search programs. The comparison result showed that CpGi is on a level with or outperforms Emboss-CpGPlot and CpG Island Searcher. Having a simple and easy-to-use user interface, CpGi would be a very useful tool for genome analysis and CpG island research. To obtain a copy of CpGi for academic use only, contact corresponding author.

Effects of Patriotism on Product Evaluation: Focused on the Mediating Effects of Consumer Ethnocentrism (애국심이 제품평가에 미치는 영향: 소비자 자민족중심주의의 매개효과를 중심으로)

  • Hong, Sung-Tai;Kang, Dong-Kyoon
    • Journal of Distribution Research
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    • v.15 no.2
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    • pp.71-99
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    • 2010
  • Most of studies on patriotism in the marketing area have focused on ethnocentric tendencies observed in consumption behaviors. On the contrary, there have been few empirical studies on how patriotism in the general sense, indicating affection for, attachment to, and pride in the country, influences consumers' evaluation of domestic and foreign products. Given the current situation that marketing activities appealing to people's patriotism is increasing, this is somewhat surprising. Thus, this study examined empirically how patriotism influences people's evaluation of domestic and foreign products. In addition, we tested whether consumer ethnocentrism works as an intervening variable in the relation between patriotism and product evaluation. The empirical analysis was conducted through a questionnaire survey of undergraduate and graduate students at universities in Seoul. The survey asked about the respondents' patriotism, consumer ethnocentrism, domestic product evaluation, foreign product evaluation, and demographical characteristics. In foreign product evaluation, the respondents were requested to evaluate Chinese and Japanese products. Email was used to send and recover the questionnaires, and 135 replies were used in the analysis. Major findings from the empirical analysis are as follows. First, a significant relationship was observed between patriotism and domestic product evaluation. That is, patriotic participants evaluated domestic products more favorably. On the other hand, no significant relationship was observed between patriotism and foreign product evaluation(See Table 1-1 and 1-2). Next, the effect of patriotism on domestic product evaluation was mediated by consumer ethnocentrism. However, whether the effect of patriotism on domestic product evaluation is mediated by consumer ethnocentrism partially or fully was different according to product(See Table 2-1 and 2-2). Lastly, we tried to analyze the relation between consumer ethnocentrism and product evaluation and comparing the results with findings of previous researches. According to the results, a significant relationship was observed between consumer ethnocentrism and domestic product evaluation but not between consumer ethnocentrism and foreign product evaluation. The meanings of this study are as follows. First, there have been few marketing studies that investigated the relation between patriotism and product evaluation. Thus, this study is meaningful in that it supplemented the limitation of previous research. Second, consumer ethnocentrism was found to mediate the relation between patriotism and domestic product evaluation. Considering the absence of previous research that examined the role of consumer ethnocentrism as an intervening variable, this study is significant in that it expanded the scope of research on consumer ethnocentrism. Third, from the practical aspect, the results of this study suggest that marketing appealing to patriotism is effective in stimulating consumers' purchase and consumption of domestic products. Accordingly, such a marketing strategy is expected to be effective in protecting domestic markets from imported goods and overseas brands and to increase demands for domestic products and brands. However, there is the question of whether the effect of patriotism based marketing strategies in promoting demand for domestic products would persist. That is, this study could not find a significant relation between patriotism and foreign product evaluation, and this means that the increase in patriotism for the home country does not damage people's view to the quality of foreign products negatively. Accordingly, without change in people's perception of foreign products, it is highly likely that the increase in demand for domestic products or brands induced by patriotism elevated at a specific time or situation may not last long. Fourth, the results of this study suggest that the patriotism level may influence consumers' choice behavior toward retailers strongly connected to a specific country or region. That is, consumers with high level patriotism may hesitate or avoid using a retailer associated with some foreign country. Fifth, according to the results of this study, when people's patriotism is stimulated by a specific social situation or event, it can be an opportunity for domestic franchise brands to increase their market performance such as sales and market share and, at the same time, for foreign franchise brands to experience adversities. Therefore, during a period like the Olympic Games or the World Cup when people's sense of belonging or attachment to their country is heightened, domestic franchise brands need to make marketing activities that may lead market opportunities to substantial results and foreign franchise brands to cope with such adversities. Sixth, consumers' brand choice is often made in retail stores. It has been demonstrated by numerous studies that in store stimuli such as point of purchase display can affect consumers' behavior. Considering this, domestic brands facing competition with foreign brands should make continuous efforts to enhance the market performance of their products through developing in store stimuli that can stimulate consumers' patriotism. Finally, based on the major findings of this study, both academic and practical issues were discussed. Suggestions for future studies were provided.

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A Collaborative Filtering System Combined with Users' Review Mining : Application to the Recommendation of Smartphone Apps (사용자 리뷰 마이닝을 결합한 협업 필터링 시스템: 스마트폰 앱 추천에의 응용)

  • Jeon, ByeoungKug;Ahn, Hyunchul
    • Journal of Intelligence and Information Systems
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    • v.21 no.2
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    • pp.1-18
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    • 2015
  • Collaborative filtering(CF) algorithm has been popularly used for recommender systems in both academic and practical applications. A general CF system compares users based on how similar they are, and creates recommendation results with the items favored by other people with similar tastes. Thus, it is very important for CF to measure the similarities between users because the recommendation quality depends on it. In most cases, users' explicit numeric ratings of items(i.e. quantitative information) have only been used to calculate the similarities between users in CF. However, several studies indicated that qualitative information such as user's reviews on the items may contribute to measure these similarities more accurately. Considering that a lot of people are likely to share their honest opinion on the items they purchased recently due to the advent of the Web 2.0, user's reviews can be regarded as the informative source for identifying user's preference with accuracy. Under this background, this study proposes a new hybrid recommender system that combines with users' review mining. Our proposed system is based on conventional memory-based CF, but it is designed to use both user's numeric ratings and his/her text reviews on the items when calculating similarities between users. In specific, our system creates not only user-item rating matrix, but also user-item review term matrix. Then, it calculates rating similarity and review similarity from each matrix, and calculates the final user-to-user similarity based on these two similarities(i.e. rating and review similarities). As the methods for calculating review similarity between users, we proposed two alternatives - one is to use the frequency of the commonly used terms, and the other one is to use the sum of the importance weights of the commonly used terms in users' review. In the case of the importance weights of terms, we proposed the use of average TF-IDF(Term Frequency - Inverse Document Frequency) weights. To validate the applicability of the proposed system, we applied it to the implementation of a recommender system for smartphone applications (hereafter, app). At present, over a million apps are offered in each app stores operated by Google and Apple. Due to this information overload, users have difficulty in selecting proper apps that they really want. Furthermore, app store operators like Google and Apple have cumulated huge amount of users' reviews on apps until now. Thus, we chose smartphone app stores as the application domain of our system. In order to collect the experimental data set, we built and operated a Web-based data collection system for about two weeks. As a result, we could obtain 1,246 valid responses(ratings and reviews) from 78 users. The experimental system was implemented using Microsoft Visual Basic for Applications(VBA) and SAS Text Miner. And, to avoid distortion due to human intervention, we did not adopt any refining works by human during the user's review mining process. To examine the effectiveness of the proposed system, we compared its performance to the performance of conventional CF system. The performances of recommender systems were evaluated by using average MAE(mean absolute error). The experimental results showed that our proposed system(MAE = 0.7867 ~ 0.7881) slightly outperformed a conventional CF system(MAE = 0.7939). Also, they showed that the calculation of review similarity between users based on the TF-IDF weights(MAE = 0.7867) leaded to better recommendation accuracy than the calculation based on the frequency of the commonly used terms in reviews(MAE = 0.7881). The results from paired samples t-test presented that our proposed system with review similarity calculation using the frequency of the commonly used terms outperformed conventional CF system with 10% statistical significance level. Our study sheds a light on the application of users' review information for facilitating electronic commerce by recommending proper items to users.