• Journal of the Korean Society of Clothing and Textiles
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• v.41 no.1
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• pp.170-183
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• 2017

The rapid growth of digital consumption has significantly changed the shopping behavior of consumers. The consumption paradigm is changing; subsequently, an omni-channel has been introduced that empowers consumers to interact with firms through a myriad of touch points in multiple channels. This study is to understand the perceptions and behavioral characteristics of consumers in the purchase process (e.g., information search and purchase phase). A qualitative method was adopted for this study and data were collected through semi-structured in-depth interviews with 15 omni-channel consumers. The results of this study were as follows. At the information search stage, consistency was the most important consideration for consumers who also wanted to retain channel-specific benefits. Consumers also searched for differentiated information among distribution channels. At the purchase stage, participants choose a shopping channel according to shopping values. They utilized newly introduced services (e.g., "online purchase, offline pick-up", FinTech) that combine retail channels. Our findings provide significance in managing omni-channel services. First, it is recommended that fashion retailers provide seamlessly integrated experience to consumer and adopt a consumer-centered channel choice strategy. Second, fashion retailers must maintain a constant attitude toward shopping experience to fashion, such as shopping enjoyment and exclusiveness.

• Journal of Korean Library and Information Science Society
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• v.37 no.2
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• pp.317-343
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• 2006

The purpose of this study is to analyze the characteristics of OPAC displays of three children's libraries in Korea: Seoul Children's Library, Cheongju Miracle Library, and Yongsan Public Library. 'OPAC Display Guidelines( Draft)' Published by IFLA is used to examine the details of OPAC displays, and to suggest their improvement. Discussed are such topics as the features of basic and detailed search screens, the brief display of search results, the arrangement and full display of bibliographic records, and the use of terms and labels. All three libraries offer their users the same KOLAS' OPAC, only designed to serve general users rather than children, i.e., their primary user group. They show some weakness, and much improvement is urgently required to satisfy specifically the needs and information seeking behavior of children.

• Journal of Intelligence and Information Systems
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• v.12 no.3
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• pp.95-110
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• 2006

To enhance the rule-based reasoning capability of Semantic Web, the XRML (eXtensible Rule Markup Language) approach embraces the meta-information necessary for the extraction of explicit rules from Web pages and its maintenance. To effectuate the automatic identification of rules from unstructured texts, this research develops a framework of using rule ontology. The ontology can be acquired from a similar site first, and then can be used for multiple sites in the same domain. The procedure of ontology-based rule identification is regarded as a graph search problem with incomplete nodes, and an A* algorithm is devised to solve the problem. The procedure is demonstrated with the domain of shipping rates and return policy comparison portal, which needs rule based reasoning capability to answer the customer's inquiries. An example ontology is created from Amazon.com, and is applied to the many online retailers in the same domain. The experimental result shows a high performance of this approach.

• Journal of Korean Society of Archives and Records Management
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• v.14 no.4
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• pp.127-151
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• 2014

To search based on the functional classification or provenance is not easy for users, and the key word-based information retrieval presents only simple words matching with the title of the records. The Presidential Archive of Korea developed a subject classification scheme to improve the convenience of searching for various records and came up with a subject thesaurus based on the scheme that utilizes the terms appearing on the title of the records and the terms used by the users who searched the portal or requested information disclosure. This research presents the development process of subject thesaurus. It also presents the utilization methods for records management work and services.

• Journal of the Korea Society of Computer and Information
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• v.26 no.8
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• pp.39-46
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• 2021

When conducting social big data analysis for franchise stores, reviews of multiple branches of a franchise can be collected together, from which analysis results can be distorted significantly. To improve its accuracy, it should be possible to filter reviews of other branches properly which are not subject to the analysis. This paper presents a method for social big data analysis which reflects characteristics of franchise stores. The proposed method consists of search key configuration and review filtering. For the former, the open data provided by Small Business Promotion Agency is used to extract region names for collecting reviews more accurately. For the latter, open search APIs provided by Naver or Kakao are used to obtain franchise branch information for filtering reviews of other branches that are not subject to analysis. To verify performance of the proposed method, experiments were conducted based on real social reviews collected from online, where the results showed that the accuracy of the proposed review filtering was 93.6% on the average.

• Annual Conference of KIPS
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• 2022.11a
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• pp.465-467
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• 2022

Mobile phones have become an essential item nowadays since it provides access to online platform and service fast and easy. Coming to these platforms such as Social Network Service (SNS) for shopping have been a go-to option for many people. However, searching for a specific fashion item in the picture is challenging, where users need to try multiple searches by combining appropriate search keywords. To tackle this problem, we propose a system that could provide immediate access to websites related to fashion items. In the framework, we also propose a deep learning model for an automatic analysis of image contexts using instance segmentation. We use transfer learning by utilizing Deep fashion 2 to maximize our model accuracy. After segmenting all the fashion item objects in the image, the related search information is retrieved when the object is clicked. Furthermore, we successfully deploy our system so that it could be assessable using any web browser. We prove that deep learning could be a promising tool not only for scientific purpose but also applicable to commercial shopping.

• Journal of Microbiology and Biotechnology
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• v.16 no.2
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• pp.178-183
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• 2006

Microbes are one of the most important bioresources in bioindustry and provide high economic values. Although there are currently about 6,000 bacterial species with validly published names, microbiologists generally assume that the number may account for less than 1% of the bacterial species present on Earth. To discover the remaining species, studies of metagenomes, metabolomes, and proteomes related to microbes have recently been carried out in various fields. We have constructed an information system that integrates various data on microbial resources and manages bioinformation to support efficient research of microorganisms. We have designated this system 'Bio-Meta Information System (Bio-MIS).' Bio-MIS consists of an integrated microbial resource database, a microbial resource input system, an integrated microbial resource search engine, a microbial resource online distribution system, a portal service, and management via the Internet. In the future, this system is expected to be connected with various public databases. We plan to implement useful bioinformatics software for analyzing microbial genome resources. The Web site is accessible at http://biomis.probionic.com.

• Journal of Information Processing Systems
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• v.16 no.1
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• pp.201-209
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• 2020

The graph data structure is popular because it can intuitively represent real-world knowledge. Graph databases have attracted attention in academia and industry because they can be used to maintain graph data and allow users to mine knowledge. Mining reachability relationships between two nodes in a graph, termed reachability query processing, is an important functionality of graph databases. Online traversals, such as the breadth-first and depth-first search, are inefficient in processing reachability queries when dealing with large-scale graphs. Labeling schemes have been proposed to overcome these disadvantages. The state-of-the-art is the 2-hop labeling scheme: each node has in and out labels containing reachable node IDs as integers. Unfortunately, existing 2-hop labeling schemes generate huge 2-hop label sizes because they only consider local features, such as degrees. In this paper, we propose a more efficient 2-hop label size reduction approach. We consider the topological sort index, which is a global feature. A linear combination is suggested for utilizing both local and global features. We conduct experiments over real-world and synthetic directed acyclic graph datasets and show that the proposed approach generates smaller labels than existing approaches.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.17 no.2
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• pp.43-64
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• 2006

Five cultural websites are evaluated on their content, interface, design. system, and service elements. The Culture Portal of Korea, Korea Culture Content, Culture Arts, Korea National Heritage Online, and Culture Heritage Information Center are chosen for this study. Most websites do not have a purpose or target audience. Their focuses are not on the content they provide but on the function of interfaces and interface design. However, interfaces do not function well for users to quickly access information they want. Suggestions are made to facilitate a system's search function and interactive users' feedback.

• Asia Marketing Journal
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• v.13 no.3
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• pp.209-231
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• 2011

Internet is having strong impact on the consumer's decision making process. Information search has been done actively through internet today. The online reviews can be crucial information cue to evaluate the alternarive products. The online WOM(Word-Of-Mouth) effect depends on the characteristics of information sender, receiver, and WOM. This study is to examine the influence of the online word of mouth on the consumer purchase intention and the moderating role of product involvement, consumer regulatory focus and self-efficacy. Positive customer reviews on the products influence the purchase intention positively and negative customer reviews influence it negatively. Moderating role of involvement in the causal relation between the valence of online reviews and purchase intention is tested. In case of positive WOM, it is predicted that purchase intention for high involvement products is higher than that of low involvement. In case of negative WOM, purchase intention for high involvement product is lower than that of low involvement product. And this study invetigate the moderating role of regulatory focus. In case of positive WOM, it is predicted that promotion focus oriented consumers have higher purchase intention than prevention focus oriented consumers. In case of negative WOM, prediction is that prevention focus oriented consumers have lower purchase intention than promotion focus oriented consumers. Then we examine the moderating role of self efficacy in the causal relation between the valence of online reviews and purchase intention. In case of positive WOM, it is predicted that consumers with low self efficacy have higher purchase intention than consumers with high self efficacy. In case of negative WOM, it is predicted that consumers with low self efficacy have lower purchase intention than consumers with high self efficacy. Emprical results support our prediction and four hypotheses derived from our conceptual framework are all accepted. This study suggest that the level of product involvement, consumer regulatory focus and the level of self-efficacy influence the consumer responses of the valence of online reviews. Therefore marketers need to manage online reviews based on the level of product involvement, regulatory focus orientation and the level of self-efficacy of target consumers.