• Journal of the Korea Society of Computer and Information
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• v.27 no.9
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• pp.59-68
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• 2022

A recommender system covers users, searches the items or services which users will like, and let users purchase them. Because recommendations from a recommender system are predictions of users' preferences for the items which they do not purchase yet, it is rarely possible to be drawn a perfect answer. An evaluation has been conducted to determine whether a prediction is right or not. However, it can be lower user's satisfaction if a recommender system focuses on only the preferences, that is caused by a 'filter bubble effect'. The filter bubble effect is an algorithmic bias that skews or limits the information an individual user sees on the recommended list. It is the reason why multiple metrics are required to evaluate recommender systems, and a diversity metrics is mainly used for it. In this paper, we compare three different methods for enhancing diversity for personalized recommendation - bin packing, weighted random choice, greedy re-ranking - with a practical e-commerce data acquired from a fashion shopping mall. Besides, we present the difference between experimental results and F1 scores.

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.2
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• pp.111-124
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• 2011

The apartment' share of the housing has steadily increased and property assets have been valued in importance as the one of asset value. Information retrieval system using internet is particularly active in the real estate market. However, user satisfaction on real estate information system is not very high, and there is a lack of research on real estate retrieval to increasing efficiency until now. This study presents a new knowledge information system developed to consider region-related factor and individual-related factor in the real estate market. In addition it enables a real estate knowledge system to search various preferential requirements for buyers such as school district, living convenience, easy maintenance as well as price. We made a survey of the search condition preference of experts on 30 real estate agents and then analyzed the result using AHP methodology. Furthermore, this research is to build apartment ontology using semantic web technologies to standardize various terminologies of apartment information and to show how it can be used to help buyers find apartments of the interest. After designing architecture of a real estate knowledge information system, this system is applied to the Busan real estate market to estimate the solutions of retrieval through Multi-Attribute Decision Making(MADM). Based on the results of the analysis, we endowed the buyer and expert's selected factors with weights in the system. Evaluation results indicate that this new system is to raise not only the value satisfaction of user, but also make it possible to effectively search and analyze the real estate through entropy analysis of MADM. This new system is to raise not only the value satisfaction of buyer's real estate, but also make it possible to effectively search and analyze the related real estate, consequently saving the searching cost of the buyers.

• The Journal of the Korea Contents Association
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• v.11 no.11
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• pp.1-9
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• 2011

With the development of next IT convergence technology and the construction of infrastructure for personalized healthcare services, the importance of services based on user's preference is being spotlighted. Healthcare service have been progressed as treatment and management for specific diseases and dietary nutrition managements to customers according to the increase in chronic patients. In this paper, we proposed the personalized dietary nutrition contents recommendation using the hybrid filtering for managing health. The proposed method uses the hybrid filtering through combining the collaborative filtering and the image filtering in order to reinforce the special trend that recommendation provides similar contents. We developed the Web application for this purpose, and experimented with it to verify the logical validity and effectiveness. Accordingly, the satisfaction and the quality of services will be improved the healthcare by recommending the dietary nutrition contents. This evaluation found that the difference of satisfaction by service was statistically meaningful and showed high satisfaction.

• Fashion & Textile Research Journal
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• v.18 no.3
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• pp.363-373
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• 2016

This study aims to develop an all-fabric integrated smart jacket in order to create a temperature-regulating system based on a user experience design. For this research, previous research technologies of a textile switch interface and a temperature-regulating system were utilized and a unifying technology for the all-fabric integrated smart jacket was developed which can provide the appropriate temperature environments to the human body. A self-heating textile was applied at the areas of the back and hood in the final tested jacket, and an embroidery circuit was developed in the form of a rectangle in the back and in both ears of the hood, taking into account the pattern of the jacket part where it was be applied and the embroidery production method. The textile switch interface was designed in a three-layer structure: an embroidery circuit line in a conductive yarn, an interval material, and a conductive sensing material, and it was made to work with the input and output sensors through the multiple input method. After the all-fabric integrated smart jacket was produced according to the pattern, all of the textile band lines for transmission were gathered and connected with a miniature module for controlling temperature and then integrated into the inside of the left chest pocket of the jacket. After the users put on this jacket, they were asked to assess the wearing satisfaction. Most of them reported a very low level of irritation and discomfort and said that the jacket was as comfortable as everyday clothing.

• Journal of Digital Convergence
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• v.15 no.1
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• pp.427-433
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• 2017

Mobile game users tend to value the opinions from their friends or SNS when making a decision on which game to play. This is because they are not satisfied with the information on suggestions provided by the conventional mobile game recommendation systems. In this research, we made a system that can reflect user preference directly by using Analytic Hierarchy Process(AHP). In the system, the hierarchy of AHP is composed of final goal(Level 1), evaluation basis(Level 2) and alternative(Level 3). And the system is made up of an input module, an AHP processing module, a recommendation module and database. Through comparison analysis with two conventional systems to test the performance of the system, we could find that the system got more higher satisfaction than the other systems.

• The Journal of the Convergence on Culture Technology
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• v.6 no.4
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• pp.477-482
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• 2020

Currently, suggesting directions for strengthening publicity of social services is thinking in the direction of each person's advantage from the stakeholder's perspective. The position of the service provider and the position of the user shows different opinions on the definition and evaluation of publicity of the city or province as the management entity. Therefore, this study combines opinions on publicity focusing on community service, derives consensus on the definition and evaluation of publicity, and evaluates different indicators or factors that cannot be quantified at the same time. The goal is to solve the problem of publicity by applying the Analytic Hierarchy Process(AHP) as a possible technique. In addition, in order to achieve the research objectives according to the designed frame, an empirical study was conducted by conducting a pairwise comparison questionnaire for experts and users. Through the AHP evaluation model" developed in this study, as a result of measuring the relative satisfaction of major factors, service utilization rate (0.470), facility management (0.210), and other project implementations (0.073) appeared in order. Here, the service utilization rate was evaluated as the most important.

• Journal of the Korean Society for Library and Information Science
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• v.52 no.3
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• pp.5-33
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• 2018

In this paper, we analyze a user's usage behavior, identify and track search intention and interest field based on the National Science and Technology Standard Classification, and use it to personalize science and technology information. In other words, we sought to satisfy both efficiency and satisfaction in searching for information that users want by improving scientific information search performance. We developed the personalization service of science and technology information and evaluated the suitability and usefulness of personalized information by comparing the search performance between expert experimental group and control group. As a result, the personalization service proposed in this study showed better search performance than comparative service and proved to provide higher usability.

• Korean Journal of Cognitive Science
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• v.12 no.4
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• pp.11-27
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• 2001

Machine translation (MT) quality assessment is an outstanding problem. In the present situation in which the quality of machine-translated products are far from the user\\`s satisfaction objective evaluation of MT system is a prerequisite to building mutual trust between the users and the vendors stimulating constructive competition among the developers and finally leading to improve the quality of MT systems. Especially there emerges a need for an intensive study on how to evaluate the quality of MT systems from both linguistic and data processing aspects and to secure a steady improvement of the translation quality. With due regard to such points we in this paper present a linguistic evaluation of English-to-Korean machine translation based on a test suite composed of 3.373 sentences that were classified into their linguistic phenomena and complexity levels and report the experimental results made from several commercial MT systems.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.89-103
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• 2019

Recently, various approaches to recommendation systems have been studied in terms of the quality of recommendation system. A recommender system basically aims to provide personalized recommendations to users for specific items. Most of these systems always recommend the most relevant items of users or items. Traditionally, the evaluation of recommender system quality has focused on the various predictive accuracy metrics of these. However, recommender system must be not only accurate but also useful to users. User satisfaction with recommender systems as an evaluation criterion of recommender system is related not only to how accurately the system recommends but also to how much it supports the user's decision making. In particular, highly serendipitous recommendation would help a user to find a surprising and interesting item. Serendipity in this study is defined as a measure of the extent to which the recommended items are both attractive and surprising to the users. Therefore, this paper proposes an application of serendipity measure to recommender systems to evaluate the performance of recommender systems in terms of recommendation system quality. In this study we define relevant or attractive unexpectedness as serendipity measure for assessing recommendation systems. That is, serendipity measure is evaluated as the measure indicating how the recommender system can find unexpected and useful items for users. Our experimental results show that highly serendipitous recommendation such as item-based collaborative filtering method has better performance than the other recommendations, i.e. user-based collaborative filtering method in terms of recommendation system quality.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.7C
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• pp.619-626
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• 2012

With the service suggesting additional extended or related query, search engines aim to provide their users more convenience. The extended or related query suggestion service based on popularity, or by how many people have searched on web using the query, has limitations to elevate users' satisfaction, because each user's preference and interests differ. This paper will demonstrate the design and realization of the system that suggests extended query appropriate for users' demands, and also an improvement in the computing process between entering the first search word and the subsequent extension to the related themes. According to the evaluation the proposed system suggested 41% more extended or related query than when searching on Google, and 48% more than on Yahoo. Also by improving the shortcomings of the extended or related query system based on general popularity rather than each user's preference, the new system enhanced users' convenience further.