• Advances in Computational Design
• /
• v.7 no.2
• /
• pp.139-151
• /
• 2022

The article is devoted to the actual problem of studying the possibilities of implementing personalization of the user interface in accordance with the personality psychotypes. The psychological aspect of user interface design tools is studied and the correspondence of their application to the manifestations of personality psychotypes is established. The results of the distribu-tion of attention of users of these categories on the course page of the educational platform are presented and the distribution of attention in accordance with the focus on educational material is analyzed. Individual features and personal preferences regarding the used design tools are described, namely the use of accent colors in interface design, the application of the prin-ciples of typographic hierarchy, and so on. In accordance with this, the prospects for implementing personalization of the user interface of the educational platform are described. The results of the study allow us to state the relevance of developing and applying personalization of the user interface of an educational platform to improve learning outcomes in accordance with the psychological impact of individual design tools, and taking into account certain features of user categories. The research is devoted to the study of user attention concentration using heatmaps, in particular based on eyetreking technology, we will investigate the distribution of user attention on the course page of an educational platform Ta redistribution of atten-tion in accordance with certain categories of personality psychotypes. The results of the study can be used to rearrange the LMS Moodle interface according to the user's psychotype to achieve the best concentration on the training material. The obtained data are the basis for developing effective user interfaces for personalizing educational platforms to improve the quality of the education.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.40 no.4
• /
• pp.154-163
• /
• 2017

Collaborative filtering, one of the most widely used techniques to build recommender systems, is based on the idea that users with similar preferences can help one another find useful items. Credit card user behavior analytics show that most customers hold three or less credit cards without duplicates. This behavior is one of the most influential factors to data sparsity. The 'cold-start' problem caused by data sparsity prevents recommender system from providing recommendation properly in the personalized credit card recommendation scenario. We propose a personalized credit card recommender system to address the cold-start problem, using multiple user profiles. The proposed system consists of a training process and an application process using five user profiles. In the training process, the five user profiles are transformed to five user networks based on the cosine similarity, and an integrated user network is derived by weighted sum of each user network. The application process selects k-nearest neighbors (users) from the integrated user network derived in the training process, and recommends three of the most frequently used credit card by the k-nearest neighbors. In order to demonstrate the performance of the proposed system, we conducted experiments with real credit card user data and calculated the F1 Values. The F1 value of the proposed system was compared with that of the existing recommendation techniques. The results show that the proposed system provides better recommendation than the existing techniques. This paper not only contributes to solving the cold start problem that may occur in the personalized credit card recommendation scenario, but also is expected for financial companies to improve customer satisfactions and increase corporate profits by providing recommendation properly.

• Journal of the Korean Society for Library and Information Science
• /
• v.35 no.3
• /
• pp.173-189
• /
• 2001

This paper presents a framework for observable behavior that can be used as a basis for user modeling, and it reports the results of a pair of user studies that examine the joint utility of two specific behaviors. User models can be constructed by hand, or they can be teamed automatically based on feedback provided by the user about the relevance of documents that they have examined. By observing user behavior, it is possible to obtain implicit feedback without requiring explicit relevance judgments. Four broad categories of potentially observable behavior are identified : examine, retain, reference, and annotate, and examples of specific behaviors within a category are further subdivided based on the natural scope of information objects being manipulated . segment object, or class. Previous studies using Internet discussion groups (USENET news) have shown reading time to be a useful source of implicit feedback for predicting a user's preferences. The experiments reported in this paper extend that work to academic and professional journal articles and abstracts, and explore the relationship between printing behavior and reading time. Two user studies were conducted in which undergraduate students examined articles or abstracts from the telecommunications or pharmaceutical literature. The results showed that reading time can be used to predict the user's assessment of relevance, that the mean reading time for journal articles and technical abstracts is longer than has been reported for USENET news documents, and that printing events provide additional useful evidence about relevance beyond that which can be inferred from reading time. The paper concludes with a brief discussion of the implications of the reported results.

• Journal of the Korea Society of Computer and Information
• /
• v.26 no.6
• /
• pp.115-127
• /
• 2021

It is not an easy task for a user to find the correct documents that a user really wanted at once from a vast amount of the search results. For this reason, various methods of recommending documents by taking the user's preferences into consideration based on the user's document browsing history have been proposed. However, the document recommendation methodology based on the document browsing history also has a limitation that only the information the user has viewed is utilized, but the intent of the user searching for the document is not fully utilized. Therefore, we propose a document recommendation method based on the user's search intent that utilizes information on "Why" the user reads the document, instead of the information on "Who" reads the document. In order to confirm the feasibility of the proposed methodology, an experiment was conducted by analyzing 239,438 actual user's search history of one of the most popular e-commerce platform companies in Korea. As a result, our methodology showed superior performance compared to the existing content-based or simple browsing history-based recommendation model.

• Science of Emotion and Sensibility
• /
• v.11 no.4
• /
• pp.521-530
• /
• 2008

Graphical user interface design, the visual language to convey information about the icon and the user's information is a medium that can lead to action. Graphical user interface to communicate with the user icon, the user is easy to use, so any time you want to provide information effectively. Communication in order to increase the efficiency of the Graphic User Interface on the nature of the medium must be made to develop the appropriate icon. In this research icon of the type of icon painting. A picture of the icon representation of each type of detail, according to a rating of johyeongjeok identify the elements of the correlation between. On the type of representation of each of Art and Design elements that I know what I saw. The icon design based on user preferences provide guidance on the direction of design-oriented. When the data can be used to designs based on the theory has to offer.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.32 no.7B
• /
• pp.438-447
• /
• 2007

In the Internet, an identity service must to obtain permission from a user to allow them to share data with requesting service. For that, the privacy policy, which reflects legal regulations and preferences made by the user, is needed. Also, the management interface that aids the user to make the privacy policy and the PDP system that makes admission control and policy decisions in response to a request from an entity wanting to access the personal information are needed. In this paper, the privacy controller system model handled under the internet Identity management system environment is proposed. The system has the easy interface of policy generation and the efficient policy decision process. The system applies and modifies to the XACML of OASIS group. We propose that the privacy policy is divided into the three policies, which are the user policy, the domain policy and the basic offering policy. To resolve the collision between the policies, we also propose the collision resolution policy.

• Journal of the Architectural Institute of Korea Planning & Design
• /
• v.36 no.4
• /
• pp.103-111
• /
• 2020

Perforated metal sheets are used as panels of facades for controlling environmental factors while ensuring user's visibility. Despite their functional potentials, only a specific direction of facades or an orientation of a building was considered in the relevant studies. This study proposed a design methodology for the perforated panel facades that reflects the location on the facades and the user's requirements. The optimization of quantitative and qualitative performance is achieved through communication between designers and users in a VR system. In optimizing quantitative performances, designers use machine learning techniques such as clustering and genetic algorithm to allocate optimal panels on the facades. In optimizing qualitative performances, through the VR system, users intervene in evaluating performances whose preferences are depending on them. The experiment using the office project showed that designers were able to make decisions based on clustering using GMM to optimize multiple quantitative performances. The gap between the target and final performance could be narrowed by limiting the types of perforated panels considering mass customization. In assessing visibility as a qualitative performance, users were able to participate in the design process using the VR system.

• Proceedings of the Korean Society for Information Management Conference
• /
• 1999.08a
• /
• pp.157-162
• /
• 1999

본 연구는 분산환경에서 이용자가 다수의 데이터베이스를 개별적으로 검색할 매와 통합적으로 검색할 때에 유용성과 이용자선호도, 이용자 만족도를 비교 분석하였다. 본 연구에는 럿거스대학 School of Communication, Information, and Library Studies에 재학중인 28명의 대학원생들이 참가하였다. 두 시스템에 대한 이용자선호도와 만족도에는 통계적으로 유의한 차이가 있는 것으로 나타났다. 즉, 많은 참가자들이 통합인터페이스보다 분리인터페이스를 선호하였고, 분리인터페이스의 검색결과에 더 만족하였다. 통합인터페이스의 편리함과 능률성에도 불구하고 참가자들이 분리인터페이스를 선호한 주된 이유중의 하나는 데이터베이스를 이용자 스스로 선택하고 통제할 수 있기 때문인 것으로 나타났다.

• International Journal of Advanced Culture Technology
• /
• v.1 no.2
• /
• pp.1-6
• /
• 2013

In this paper, we evaluate performance of existing similarity measurement metric and propose a novel method using user's preferences information entropy to reduce MAE in memory-based collaborative recommender systems. The proposed method applies a similarity of individual inclination to traditional similarity measurement methods. We experiment on various similarity metrics under different conditions, which include an amount of data and significance weighting from n/10 to n/60, to verify the proposed method. As a result, we confirm the proposed method is robust and efficient from the viewpoint of a sparse data set, applying existing various similarity measurement methods and Significance Weighting.

• Proceedings of the Korea Contents Association Conference
• /
• 2016.05a
• /
• pp.445-446
• /
• 2016

이모티콘은 자신의 감정과 개성을 표현하는 중요한 수단이 되었다. 그러나 이모티콘의 수가 너무 많아 이에 따른 적절한 이모티콘을 선택하기가 어려워 졌다. 따라서 본 제안에서는 사용자에 선호도에 따라 이모티콘을 제안하여 보다 손쉬운 인터페이스를 제공하고자 한다.