• Asia pacific journal of information systems
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• v.12 no.1
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• pp.1-16
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• 2002

Most of searching systems used by shopping-mall provide too much information for user requirements or fail to provide appropriate items reflecting customer's preference. This paper aims to design and implement the product searching systems based on customer preference which will enable efficient product selection in the internet shopping-mall. The proposed system consists of user/provider interface, searching and model agent, data management system, and model management system. Especially, we construct the searching pattern database to support fast search using association mining method. And this system includes the customer-oriented decision model which shows the highly preferred products. Input weight value per attribute and preference level should be needed to compute priority grade of preference.

• Journal of Korea Multimedia Society
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• v.7 no.2
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• pp.145-155
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• 2004

It is very important for Internet searching systems to have user-friendly and rapid searching functions at the managers'point of view. The former finds optimized input parameters to support the various searching requirements of user. The latter has fast searching results which are effectively normalized to various input parameters having different attributes. In this paper we basically focus on optimized database construction not only to have searching functions with multiple attributes to support maximal various input requirements of the user but also to have more rapid searching functions. For this research, we suggest a modified association algorithm that takes into consideration to the support and confidence that is the criteria of the association mining rule in order to reflect the searching characteristics of internet shopping malls. We also propose the model management systems for rapid searching functions. The following results are from a processed simulation: the more the number of searching transactions of the users increase, the less the total relative average searching time becomes.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.1
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• pp.1-9
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• 2012

It is well known that internet shoppers are very sensitive to sale prices. They visit the various shopping malls and collect the product information including purchase conditions for goods purchase decision-making. Recently the necessity of information support is increasing because of increase of information amount which is necessary and complexity of goods purchase decision-making process. The comparison shopping agent systems have provided price comparison information which is collected from various shopping malls to satisfy internet shoppers information craving. But the frequent price change caused by keen price competition is becoming the primary reason of information quality decline among price comparison sites. RSS which is a family of web feed formats used to publish frequently updated is applied even in on-line shopping malls. This paper develops a RSS product information collection system to get real-time product information. The proposed product information system consists of (1) web crawler module for searching RSS feed shopping malls automatically, (2) RSS reader module for parsing product information from RSS feed file, (3) product DB and (4) product searching module. Performance of the proposed system is higher than the comparison shopping agent systems when it is defined with the volume of collecting product information per unit time.

• Proceedings of the Korean Society for Information Management Conference
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• 1995.08a
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• pp.45-48
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• 1995

Since the early 1970s online searching has provided end-users with commercial and governmental bibliographic databases by trained intermediaries through the developed Vendor/Agency Systems. Recently, the situation has begun to change. The era of end-user searching is coming. End Users are the “information consumers” as the final user of an IT product or set of information. This study on end-user online searching is presented with the following aspects: development, characterization, training, end user online search services in university libraries, role of the intermediaries and librarians, the future.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.21 no.6
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• pp.579-587
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• 2008

In collaborative environment, since each agent generally uses different words for the same meaning, there is an obstacle for information sharing. In collaborative product development environment, each agent has different words for representing same product information. As a result, it is hard to share product information in this situation. For solving this problem, semantic-based product information is needed. In this paper, a ontology-based semantic searching system which is able to interact with legacy PDM systems is proposed for product information sharing in collaborative environment Product ontology is represented with OWL format, and the product ontology is processed by Pellet reasoning engine for semantic searching. The system is implemented as a web service which can be integrated with other systems. This paper also introduces the approach with which a PDM system provides a function of semantic search with this search system.

• Asia pacific journal of information systems
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• v.29 no.2
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• pp.248-267
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• 2019

As merging online and offline channels into one single platform, individuals could easily and frequently switch between online and offline channels. In order for understanding such unique behaviors, this study attempts to explore why and how consumers choose their channels to search and purchase a product. We have drawn on multiple theories that have been used to explain individuals' judgment and decision making (i.e., construal level theory and regula-tory focus theory) in order to develop and tested two-way ANOVA based models of how both regulatory focus (e.g., promotion vs. prevention) and product types (e.g., experience goods vs. searching goods) including the psychological distance cue separately and jointly affect individuals' channel selection behavior (e.g., intention to use single channel vs. intention to use cross-channels). Our results have indicated that consumers with promotion-focus are more likely to use a single channel in experience goods rather than in searching goods when there exists the psychological cue. Based on our findings, the implication for both research and practice are discussed.

• Asia pacific journal of information systems
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• v.15 no.1
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• pp.63-79
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• 2005

Recommender systems are a personalized information filtering technology to help customers find the products they would like to purchase. Collaborative filtering is known to be the most successful recommendation technology, but its widespread use has exposed some problems such as sparsity and scalability in the e-business environment. In this paper, we propose a recommendation system, WebCF-PT based on Web usage mining and product taxonomy to enhance the recommendation quality and the system performance of traditional CF-based recommender systems. Web usage mining populates the rating database by tracking customers' shopping behaviors on the Web, so leading to better quality recommendations. The product taxonomy is used to improve the performance of searching for nearest neighbors through dimensionality reduction of the rating database. A prototype recommendation system, WebCF-PT is developed and Internet shopping mall, EBIB(e-Business & Intelligence Business) is constructed to test the WebCF-PT system.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.05a
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• pp.316-320
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• 2005

We developed Intelligent Product Search Agent based on SWRL, and this agent can search product information with knowledge(facts and rules) on the web, implement price comparison for searched products considering delivery rates. Existing keyword based product search engines is poor at searching intent products though a user has already prefect knowledge about intent produces. Furthermore if a user has insufficient knowledge, it is impossible to implement search. Also, existing price comparison shopping mall gives users comparison service considering total price(product prices, taxes, delivery rates), this service is valid to single product and has limitations of system expansion and up-dating because of not rule base but programming base. If there is appropriate knowledge on the Semantic web and this makes product information retrieval possible, above problems can be solved clearly. In this research, we developed Intelligent Product Search Agent based on SWRL that can search product information efficiently by making agent to handle facts and rules by itself.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.1
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• pp.42-49
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• 2020

This study is an empirical research to find out the effect on the management performance of hidden champions of food manufacturing companies when using blue ocean strategy for new product development. In order to achieve the purpose of this study, we conducted a questionnaire survey on hidden champions in the domestic food manufacturing industry and proceeded empirical analysis. When small and medium-sized enterprises in food manufacturing industries develop a new product, searching for non-customer, rebuilding the market boundary, and linking the external networks have a significant impact on their management performance. However, the fair procedure did not have a significant effect on the management performance. In terms of relative influence, rebuilding the market boundary was most affecting, followed by searching for non-customer and linking the external networks. On the other hand, this study implicated the management performance of hidden champions of food manufacturing industries when new products is developed by using the blue ocean strategy. Obtained results are as follows. If small and medium-sized enterprises of food manufacturing industries develop new products, it will be able to improve the management performance by utilizing strategies such as searching for non-customer, rebuilding the market boundary, and linking the external networks. In particular, the rebuilding the market boundary among the blue ocean strategies has a relatively high impact on management performance.

• The Journal of Information Systems
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• v.20 no.3
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• pp.41-61
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• 2011

In order to buy products through the Internet, consumers dissipate much time and efforts in collecting and comparing product information from various online shopping malls. Consumers can save their efforts by using price comparison sites, but there are some shortcomings in comparison shopping. Firstly, comparison sites do not show the lowest price of some products that are selling in shopping malls. Secondly, the product information provided by comparison sites is sometimes wrong. Thirdly, there are too many results. In order to overcome the shortcomings, we suggested a comparison shopping system based on RSS by using ontology matching. We used the current RSS standard for syntactic interoperability instead of suggesting new standards. Moreover, we used ontology matching for semantic interoperability to compare product information with different ontologies. The suggested ontology matching consists of three steps. The first step is finding exact sense from WordNet for a given product category, and the second step is searching for matching product category candidates from the products of RSS feeds. The final step is calculating similarities of the candidates with the target product category. From the experiments, we could get better recall rates that are suitable for e-commerce environments and the results show that our system is effective in product comparison.