• The Transactions of the Korea Information Processing Society
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• v.6 no.7
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• pp.1832-1840
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• 1999

Since the existed Korean Web IR systems generally use boolean system, it is difficult to retrieve the information to be wanted at one time. Also, because of the feature that web documents have the frequent abbreviation and many links, the keyword extraction using the inverted document frequency extracts the improper keywords for adding ambiguous meaning problem. Therefore, users must repeat the modification of the queries until they get the proper information. In this paper, we design and implement the relevance feedback agent system for resolving the above problems. The relevance feedback agent system extracts the proper information in response to user's preferred keywords and stores these keywords in preference DB table. When users retrieve this information later, the relevance feedback agent system will search it adding relevant keywords to user's queries. As a result of this method, the system can reduce the number of modification of user's queries and improve the efficiency of the IR system.

• The KIPS Transactions:PartD
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• v.15D no.4
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• pp.463-474
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• 2008

The advancement of information technology and the popularization of Internet has explosively increased the amount of multimedia contents. Therefore, the requirement of multimedia recommendation to satisfy a user's needs increases fastly. Up to now, CF is used to recommend general items and multimedia contents. However, general CF doesn't reflect visual characteristics of image contents so that it can't be adaptable to image recommendation. Besides, it has limitations in new item recommendation, the sparsity problem, and dynamic change of user preference. In this paper, we present new image recommendation method FBCF (Feature Based Collaborative Filtering) to resolve such problems. FBCF builds new user profile by clustering visual features in terms of user preference, and reflects user's current preference to recommendation by using preference feedback. Experimental result using real mobile images demonstrate that FBCF outperforms conventional CF by 400% in terms of recommendation ratio.

• Journal of the HCI Society of Korea
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• v.11 no.2
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• pp.15-22
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• 2016

The ways to interact with digital appliances are becoming more diverse. Users can control appliances using a remote control and a touch-screen, and appliances can send users feedback through various ways such as sound, voice, and visual signals. However, there is little research on how to define which output method to use for providing feedback according to the user' input method. In this study, we designed an experimental study that seeks to identify how to appropriately match the output method - voice and sound - based on the user input - voice and button. We made four types of interaction with two kinds input methods and two kinds of output methods. For the four interaction types, we compared the usability, perceived satisfaction, preference and suitability. Results reveals that the output method affects the ease of use and perceived satisfaction of the input method. The voice input method with sound feedback was evaluated more satisfying than with the voice feedback. However, the keying input method with voice feedback was evaluated more satisfying than with sound feedback. The keying input method was more dependent on the output method than the voice input method. We also found that the feedback method of appliances determines the perceived appropriateness of the interaction.

• Science of Emotion and Sensibility
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• v.25 no.3
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• pp.3-14
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• 2022

With the increase of video conferencing users and the development of technology, the situations where video conferencing is used and the layout of video conferencing interfaces are diversifying. Social anxiety affects video conferencing communication and is closely related to the self-view function, which is characteristic of video conferencing. The self-view function is part of the video conferencing interface that provides a small preview of one's own camera feed. Self-view is known to degrade work performance and cause fatigue; however, it is set as the default function on video conferencing software in a way that users generally prefer. This study used an online survey to study the effect of task orientation, preferred self-view size, and social anxiety on video feedback preference. Participants responded to questions assessing work orientation, social anxiety level, preferred self-view size, and self-view preference. The results showed that preferred self-view size mediates task orientation and video feedback preference. There was no significant difference in the mediating effect of the preferred self-view size according to the degree of social anxiety. These results offer insights into the interactions between users and video conferencing software and provide information that can be useful for designing video conferencing interfaces.

• Current Research on Agriculture and Life Sciences
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• v.25
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• pp.19-23
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• 2007

This research to streets at Daegu, and view adjective how people react when draw a bird into interior in city utilize and examine becoming direction of street trees system. Findings on survey, citizens appear by average 2.87 in management degree of street trees and average 2.76 in various of species of trees, discontent thing more or less by average 2.91 in satisfaction of the beauty, and demonstrate high shame from satisfaction for season stuff to comparative high 3.24, generally, citizens appear by there are parts to improve by do dissatisfaction about street trees system at Daegu. Also, street trees 2 lines plantings for a bird is average 3.05, shows affirmative feedback about that shrub utilization for a bird see high numerical value by average 3.4 and people draw a bird to space of city. Therefore, construct street trees friendly to the nature and be considered to need to re-establish set street trees environment in citizens preference to recover city ecosystem. As result that examine reaction which treat in street trees planting programs to draw birds into city through view adjective, Likert scales about 2 lines plantings of street trees and additional planting of shrub show affirmative feedback by average 3.4 both ordinary people and specialist group, if people want to draw birds into city by various of method, various research should be accomplished.

• Journal of KIISE:Software and Applications
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• v.31 no.8
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• pp.1062-1072
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• 2004

Collaborative filtering systems based on ｛user-document｝ matrix are effective in recommending web documents to user. But they have a shortcoming of decreasing the accuracy of recommendations by the first rater problem and the sparsity. This paper proposes the automatic preference rating method that generates user profile to solve the shortcoming. The profile in this paper is content-based collaborative user profile. The content-based collaborative user profile is generated by combining a content-based user profile with a collaborative user profile by mutual information method. Collaborative user profile is based on ｛user-document｝ matrix in collaborative filtering system, thus, content-based user profile is generated by relevance feedback in content-based filtering systems. After normalizing combined content-based collaborative user profiles, it automatically rates user preference by reflecting normalized profile in ｛user-document｝matrix of collaborative filtering systems. We evaluated our method on a large database of user ratings for web document and it was certified that was more efficient than existent methods.

• The Journal of the Korea Contents Association
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• v.7 no.4
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• pp.66-73
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• 2007

Internet is a part of our common life and tremendous information is cumulated. In these trends, the personalization becomes a very important technology which could find exact information to present users. Previous personalized services use content based filtering which is able to recommend by analyzing the content and collaborative filtering which is able to recommend contents according to preference of users group. But, collaborative filtering needs the evaluation of some amount of data. Also, It cannot reflect all data of users because it recommends items based on data of some users who have similar inclination. Therefore, we need a new recommendation method which can recommend prefer items without preference data of users. In this paper, we proposed the apparel coordination system using personalized preference on the semantic web. This paper provides the results which this system can reduce the searching time and advance the customer satisfaction measurement according to user's feedback to system.

• Journal of the Ergonomics Society of Korea
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• v.19 no.1
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• pp.23-36
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• 2000

In conventional ergonomics, consumer product can be made based on anthropometric data and specific design guideline. However, the product may not satisfy consumers because their emotional preference have not been properly considered in design phase. Therefore, in this study a new chair design process was introduced by which both consumer's emotional need and traditional ergonomic requirement can be satisfied. As a part of the process, the traditional Kansei engineering technique was modified to collect quantitative information of consumer's visual appreciation and physical feedback of various types of chairs. Furthermore, we developed an interface, so called, KADAS(Kamsung Analysis and Design Assistance System), for designers to use the technique in chair design. This software can help designers to understand what should be the most suitable shape in designing items such as seat, back and arm rest, etc. to meet the emotional need of consumers. This software displays the result of modified quantification theory I, and explains how to use the statistics. This study suggested a new approach for ergonomic design incorporated with Kansei Engineering technique. This technique can be also applied to other products by extending the database of KADAS.

• Journal of the Korean Society for information Management
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• v.26 no.1
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• pp.81-105
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• 2009

In this paper, we propose user contents using behavior and location information on contents on various channels, such as web, IPTV, for contents distribution. With methods to build user and contents profiles, contents using behavior as an implicit user feedback was applied into machine learning procedure for updating user profiles and contents preference. In machine learning procedure, contents-based and collaborative filtering methods were used to analyze user's contents preference. This study proposes contents location information on web sites for final recommendation contents as well. Finally, we refer to a generalized recommender system for personalization. With those methods, more effective and accurate recommendation service can be possible.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.10
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• pp.2241-2246
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• 2015

Recently for efficient management, companies have collected and investigated information about customers' feedback by using a system that analyzes big data from social media. This paper proposes more accurate and efficient evaluation method of collecting and investigating customers' feedback using social big data for travel agency, which is representative company of hospitality industry. First, it designs service model and, as a test-bed, analyzes media channel, customer satisfaction, and brand-image etc. of big 5 travel agencies in Korea. In addition, we suggest an analysis result of evaluating preference with positive rate and negative rate by proposed evaluation method. It allows a travel agency to know which area should be improved corresponding to evaluation item; thus, suggested evaluation method is effective to manage customers even more efficiently.