• Journal of the Korean Society of Clothing and Textiles
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• v.25 no.2
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• pp.206-216
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• 2001

This study was intended to identify the information search behavior according to the risk perception and clothing involvement. The data were collected via a questionnaire from 369 students of Semyung University in Checheon and data were analyzed by frequency, factor analysis, Cronbachs alpha and multiple regression. The results of this study were as follows; 1. Multiple regression revealed the fact that each type of involvement dimensions were influenced by the risk perception dimensions. Among four involvement dimensions, importance of clothing was the best influenced factor according to the risk perceptions. 2. Also information search behavior was influenced by risk perception and fashion involvement. Among four information search behaviors, industry providing search was the best influenced factor by the risk perception and clothing involvement.

• Journal of the Korean Home Economics Association
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• v.42 no.9
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• pp.195-212
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• 2004

The purpose of this study was to analyze consumers' perceived risk and information search behaviors in internet shopping. For this purpose, survey was conducted on 302 consumers in their 20s and 30s who had internet shopping experience. This study found that consumers' perceived risk was significantly related to their gender, educational level, income, credit card use, period of internet un, number of internet shopping experiences, and purchased product. Consumers' search behaviors were also significantly affected by gender, age, educational level, income, period of internet use, and purchased product. In addition, a higher level of consumers' perceived risk was significantly related to the amount of information search on product attributes themselves rather than on general information search such as the number of sites or the number of brands.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.10a
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• pp.598-601
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• 2003

As the amount of information on the WWW is increasing at a very high speed, the role of search engines has become more necessary and important. Yet, current popular search engines have a limitation of scalability because the more information those engines gather, the more garbage hit search results are produced, thus, XML based metadata has recently been the issue of much focus. Metadata is information about information, which using a small potion of data can express the fundamental information about other information. XML enables data to be expressed better organized and well structured. Moreover, the information in those current efficiency and make them disappointed by dead links and obsolete pages. this is because the information was collected and indexed in advance before users do searching. therefore, a mechanism is required that cam search from current and up-to-date information resources dynamically in real time to avoid retrieving out of data information. In this study, a new concept search agent system for the WWW by using XML based technology is proposed. the implementation of the prototype of this proposed system, the comparison with traditional search engines, and the evaluation of the prototype system are also discussed.

• Journal of Korean Library and Information Science Society
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• v.37 no.2
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• pp.127-144
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• 2006

This study intends to analyze the integrated search methods in digital libraries environment. To categorize various integration methods, I investigated the developmental properties and integration types of digital libraries from a users point of view. And then, I reviewed the current best practices of library portal which are JISC Information Environment, NSDL OCKHAM and Korea Knowledge Portal Initiatives. Nextly, I derived the two methods of Integrated search mechanisms such as aggregated search and distributed search that is useful in the digital libraries environment.

• Proceedings of the Korean Information Science Society Conference
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• 2010.06a
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• pp.246-247
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• 2010

This paper proposes a fast motion estimation algorithm based on motion speed and multiple initial center points. The proposed method predicts initial search points by means of the spatio-temporal neighboring motion vectors. A dynamic search pattern based on motion speed and the predicted initial center points is proposed to quickly obtain the motion vector. Due to the usage of the spatio-temporal information and the dynamic search pattern, the proposed method greatly accelerates the search speed while maintaining a good predicted image quality. Experimental results show that the proposed method has a good predicted image quality in terms of PSNR with less search time as compared to the Full Search, New Three-Step Search, and Four-Step Search.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.686-687
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• 2022

Existing clothing product search is possible only with text search, so it is not possible to properly search for the product that the user is looking for, and it takes a lot of time to search for the desired product. In addition, it was difficult to know where to sell unbranded products such as Soho Mall products, and it was difficult to search for detailed attributes of fashion products. To solve this problem, we would like to propose a deep learning technique that can search for the exact information that the user wants through the learned image search.

• Journal of the Korean Home Economics Association
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• v.48 no.9
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• pp.41-54
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• 2010

This study attempted to determine how the subjective knowledge related to a consumer's life cycle influences their information search in the decision making process. The data was collected using a total of 349 questionnaires for the final analysis of this study. SPSS 12.0 for windows was used for the data analysis and the detailed analyses included descriptive analysis, factor analysis, reliability tests, one way ANOVA, multiple regression analysis and t-tests. The results of this study showed that there are differences in the subdivisions of subjective knowledge of apparel according to the consumer's life cycle and there is a difference in the types of information searches according to the consumer's subjective knowledge, and the subdivisions of subjective knowledge of the consumers influence their information search. This study showed that although it affected the internal search, the media search, and the store search, it did not influence the personal search in the decision making process.

• Journal of KIISE:Databases
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• v.36 no.4
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• pp.321-326
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• 2009

Since the existing Web search engines don't sufficiently reflect user's search intent, it is very difficult to find out accurate information that users want to find. Therefore, a lot of researches, study for personalized search, to enhance satisfaction of Web search results by analyzing search pattern and applying it to search are in progress in these days. Web searchers can more efficiently find information and easily obtain appropriate information through the personalized search. In this paper, we propose the personalized search based on community through the analysis of web users' query patterns and interest. Consequently, when applying query frequency, interest and community to web search, we are able to the confirm that the search results which hit to the search intent of the individual are provided.

• Journal of the Korean Society for information Management
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• v.29 no.1
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• pp.175-190
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• 2012

This study aims to investigate the current status of mobile search functions of Korean search portals, namely Google Korea, Naver, Nate, Daum, and Yahoo Korea. This study focuses on unique mobile search functionalities, such as voice search, music search, code search, and visual/ object search. In particular, this study analyzed characteristics of these search functions and evaluated their performances based on the accuracy and the speed of recognition. The results of this study show that both Naver and Daum support various mobile searching functions, whereas Google only supports voice search. Nate and Yahoo do not offer any unique function. The results of this study can be applied to the portal's effective development of mobile search functionalities.

• Journal of the Korea Society of Computer and Information
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• v.8 no.1
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• pp.20-29
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• 2003

According as quantity of information is augmented rapidly in World Wide Web, users are investing more times finding correct information to on. Search function that a search agent is personalized according to user's preference degree or search objective to solve these problem should be offered. Therefore, a search agent accumulates experienced knowledge connected with user's past search in this research. When new query was given, search agent offered learning function of intelligence that decides category group through estimation method of similarity using this knowledge. So this paper showed that case based search can bring superior result in the correctness rate than other search method.