• KIPS Transactions on Software and Data Engineering
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• v.4 no.6
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• pp.253-260
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• 2015

When we buy items in online stores, it is common to face recommended items that meet our interest. These recommendation system help users not only to find out related items, but also find new things that may interest users. Recommendation system has been widely studied and various models has been suggested such as, collaborative filtering and content-based filtering. Though collaborative filtering shows good performance for predicting users preference, there are some conditions where collaborative filtering cannot be applied. Sparsity in user data causes problems in comparing users. Systems which are newly starting or companies having small number of users are also hard to apply collaborative filtering. Content-based filtering should be used to support this conditions, but content-based filtering has some drawbacks and weakness which are tendency of recommending similar items, and keeping history of a user makes recommendation simple and not able to follow up users preference changes. To overcome this drawbacks and limitations, we suggest weighted window assisted user history based recommendation system, which captures user's purchase patterns and applies them to window weight adjustment. The system is capable of following current preference of a user, removing useless recommendation and suggesting items which cannot be simply found by users. To examine the performance under user and data sparsity environment, we applied data from start-up trading company. Through the experiments, we evaluate the operation of the proposed recommendation system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.1
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• pp.380-386
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• 2020

The mobile application market has grown over the past decade since the advent of smartphones, making it the largest market for electronic device software. As competition intensifies in the mobile application market, the impact of application evaluations on the consumption and usage patterns of users has also significantly increased. Therefore, research has been conducted on measures to evaluate mobile applications, but most of the research has relied on qualitative methods such as expert-centered interviews or surveys. In addition, evaluation measures are being constructed from the service provider's perspective, not from the service user's perspective. However, the possibility of application-specific analyses that minimize the subjectivity of researchers is growing, as large amounts of user review data enable quantitative analysis of actual users' assessment of applications. Therefore, this study presents a methodology that can complement current problems with existing quality assessments for mobile applications by utilizing user review data. To this end, the Topic Modeling technique LDA (Latent Dirichlet allocation) is applied in order to elucidate ways to improve existing evaluation measures from a user's perspective. The study is expected to reduce bias in service assessment due to the subjectivity of service providers and researchers as well as provide a measure of assessment by area of mobile applications from a consumer perspective.

• Journal of Distribution Science
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• v.13 no.8
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• pp.97-104
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• 2015

Purpose - This study examines the positive impact of the social distance between producers and users of online content, investigating and analyzing the most popular Web content. In addition, it tries to elicit the matching effect that appears when the individuals'cultural background is consistent with social distance. Research design, data, and methodology - We collected and analyzed actual data about 4,981 videos clips on YouTube, looking at six countries in order to verify the content of this study. Based on the results of the data analysis, the study conducted behavioral measurements on popularity, social distance, culture, and user engagement. The unit of analysis was the content and we collected information about the content producers and the content records. We controlled the views, comments, likes, calendar dates, and ages in the empirical models. The data was collected in 2011, with the records coming from South Korea, Japan, China, U.S., German, and France. A total of 4,980 elements were analyzed in the model. The empirical model estimated is the bivariate negative binomial distribution (NBD) model. Results - It turns out that there is a possibility that the matching effect can be diminished by variables that reflect the psychological involvement of user engagement. This study proposes academic and practical implications based on these research results. This research shows the positive effect of social distance between users and producers on the increased performance of the online content. We find the effect of social distance to be a stronger tendency in collectivism. The collectivists follow their sense of friendship and intimacy in their culture and, the social congruence effect can be found there as well. The effect, however, could erode in a social case where users are motivated by strong intrinsic and psychological factors. In addition, user engagement complicates the process of user decision making regarding the information. Conclusions - This study examines how the differential effects of social distance caused by culture could disappear through user commitment as a complicated user motivation. Some potential implications are as follows. First, a firm in the collectivism culture has to communicate based on the social distance. In fact, most online channels do not have a function that indicates the social distance as measured by favorites or subscribers. This function could help increase the performance of the content in online channels, but this increasing effect can only be found in a collectivist culture. Based on this, the firms have to communicate and announce to users the actual social distance between users and producers. Second, firms should develop a system that discovers the social distance and culture and shows these measures to users and producers, since the congruence effect between social distance and culture is found only for low user engagement. The firms can take the advantage of the congruence effect only for the development of the social distance and culture visualized system.

• Journal of the Korea Society of Computer and Information
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• v.29 no.6
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• pp.69-76
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• 2024

Recent advances in sensor and mobile technologies have made it possible to collect user location data. This location information is used as a valuable asset in various industries, resulting in increased demand for location data collection and sharing. However, because location data contains sensitive user information, indiscriminate collection can lead to privacy issues. Recently, geo-indistinguishability (Geo-I), a method of differential privacy, has been widely used to protect the privacy of location data. While Geo-I is powerful in effectively protecting users' locations, it poses a problem because the utility of the collected location data decreases due to data perturbation. Therefore, this paper proposes a method using Geo-I technology to effectively collect user location data while maintaining its data utility. The proposed method utilizes the prior distribution of users to improve the overall data utility, while protecting accurate location information. Experimental results using real data show that the proposed method significantly improves the usefulness of the collected data compared to existing methods.

• Journal of the Korean Data and Information Science Society
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• v.27 no.6
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• pp.1557-1564
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• 2016

Recently, an extended warranty of a system following the expiration of the basic warranty is becoming increasingly popular to the user. In this respect, we suggest a two stage maintenance policy under the non-renewing warranty from the user's point of view in this paper. In the first stage, the user has to decide whether or not to purchase the extended warranty period. And, in the second stage, the optimal replacement period following the expiration of the warranty is determined. Under the extended warranty, the failed system is minimally repaired by the manufacturer at no cost to the user. We utilize the expected cost from the user's perspective to determine the optimal two stage maintenance policy. Finally, a few numerical examples are given for illustrative purpose.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.295-300
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• 2009

This paper presents a context-aware information service system in public places that have complex processes, for the disabled and the elderly. The system infers context of a user which is derived from the user's demand, then it informs to the user -what to do, where to go-according to the context. Our system gets user's context from sensor data and informations from the local information system. The system provides more suitable information with a knowledge model, which organizes location and process data coordinately. The information is provided personally to the user, with mobile devices.

• Journal of Electrical Engineering and Technology
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• v.10 no.6
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• pp.2406-2412
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• 2015

Multi-user multi-input multi-output (MU-MIMO) system has attracted the 4^th generation wireless network as one of core technique for performance enrichment. In this system rate control is a challenging problem and another problem is optimization. Proper scheduling can resolve these problems by deciding which set of user and at which rate the users send their data. This paper proposes a new multi-parameter based scheduling (MPS) for downlink multi-user multiple-input multiple-output (MU-MIMO) system under space-time block coding (STBC) transmissions. Goal of this MPS scheme is to offer improved link level performance in terms of a low average bit error rate (BER), high packet delivery ratio (PDR) with improved resource utilization and service fairness among the user. This scheme allows the set of users to send data based on their channel quality and their demand rates. Simulation compares the MPS performance with other scheduling scheme such as fair scheduling (FS), normalized priority scheduling (NPS) and threshold based fair scheduling (TFS). The results obtained prove that MPS has significant improvement in average BER performance with improved resource utilization and fairness as compared to the other scheduling scheme.

• Journal of Internet Computing and Services
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• v.10 no.1
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• pp.111-121
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• 2009

In this paper, we propose a multimedia recommender system using user's playback time. Proposed system collects multimedia content which is requested by user and its user‘s playback time, as web log data. The system predicts playback time.based preference level and related contents from collected transaction database by fuzzy association rule mining. Proposed method has a merit which sorts recommendation list according to preference without user’s custom preference data, and prevents a false preference. As an experimental result, we confirm that proposed system discovers useful rules and applies them to recommender system from a transaction which doesn‘t include custom preferences.

• Journal of the Korean Society for information Management
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• v.25 no.1
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• pp.43-59
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• 2008

This study investigated the main user types of the reading programs which are provided by sixty-two public libraries during September, "the Month of Reading," in seven metropolitan cities, Seoul. Pusan, Daegu, Incheon, Daejeon, Gwangju and Ulsan. For the analysis, the data are collected from 622 programs of "the Month of Reading." The content analysis method was used to analyze data and find meanings from it. The findings show, there are a little differences in the priority order of the main user types among the seven metropolitan cities, however, the children and all ages of the public libraries in seven metropolitan cities are identified as the main user types of the libraries.

• Journal of the Korea Society of Computer and Information
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• v.8 no.2
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• pp.8-15
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• 2003

Recently various of information suppliers provide information via WWW so the necessary of search engine grows larger. However the efficiency of most search engines is low comparatively because of using simple pattern match technique between user's query and web document. A specialized search engine returns the specialized information depend on each user's search goal. It is trend to develop specialized search engines in many countries. However, most such engines don't satisfy the user's needs. This paper proposes the specialized search engine for ocean information that uses user's query related with ocean and the association rules in web data mining can prove relation between web documents. So this search engine improved the recall of data and the precision in existent search method.