• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.2
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• pp.379-386
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• 2014

As the use of mobile device is increasing rapidly, the number of users is also increasing. However, most of the app stores are using recommendation of simple ranking method, so the accuracy of recommendation is lower. To recommend an item that is more appropriate to the user, this paper proposes a technique that reflects the weight of user information and recent preference degree of item. The proposed technique classifies the data set by categories and then derives a predicted value by applying the user's information weight to the collaborative filtering technique. To reflect the recent preference degree of item by categories, the average of items' rating values in the designated period is computed. An item is recommended by combining the two result values. The experiment result indicated that the proposed method has been more enhanced the accuracy, appropriacy, compared to item-based, user-based method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.12
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• pp.2871-2877
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• 2015

Shopping patterns are changing with the emergence of SNS. Recently, it is also interested in providing the information based on the users' needs. Generally, the provided information is obtained from the history of users' simple browsing. Best selling hot item list is also provided in order to reflect the preferences of public users. However, the provided information is irrelevant to an individual preference. In this paper, we propose a method to utilize inner and outer SNS for analyzing public preferences about goods which are interested by individual users. The inner analyzing module collects and analyzes the preferences of community members about two goods designated by individual users. The outer analyzing module supports to analyze public preferences by using the tweeter SNS. The results of implementation show that it is possible to recommend goods based on the individual users' preferences unlike the existing shopping mall.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.9
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• pp.2073-2080
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• 2015

Even though users choose goods they want to buy in on-line shopping malls, real purchase is often performed in off-line shopping malls. It is called reverse showrooming. It means that users' analysis of goods based on images and description of internet shopping malls has limitation. Thus, large-scale online shopping malls provide a customized shopping information. However, in that case, the provided information is a simple list of goods users bought or retrieved. Thus, a system to analyze various needs of users and apply the result into on-line shopping mall is necessary. In this paper, an analysis system is proposed. The system contains a module to analyze user defined preference and a module to analyze users' reviews. The former designates two goods and collects preferences of individual users. the latter analyzes reviews about purchased goods based on database dictionary stored in advance for analyzing reviews. The system implemented shows that it is possible to recommend some goods that meet each users's needs

• Information Systems Review
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• v.23 no.4
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• pp.87-102
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• 2021

Smart cities are attracting attention as a new economic growth engine based on new technologies and means to solve side effects of urbanization such as a surge in energy consumption, deepening environmental pollution, and an increase in crime rates. In particular, as demand for non-face-to-face services increases due to COVID-19, the role of smart cities that can provide various online and offline non-face-to-face services is becoming more important. Therefore, this study defined smart city non-face-to-face services based on literature research on the concept and underlying technology of smart city, and analyzed consumer utility for each service using Conjoint analysis. In particular, differences in user preferences between Sejong City and Busan City, which are currently designated as national smart city pilot cities in Korea, were compared and analyzed, and based on the derived results, measures to improve the competitiveness of smart city services were suggested.