• Journal of the Korean Data and Information Science Society
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• v.22 no.1
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• pp.19-27
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• 2011

Recommendation systems are developed to overcome the problems of selection and to promote intention to use. In this study, we propose a recommendation system using adjacency data according to user's behavior over time. For this, the product adjacencies are identified from the adjacency matrix based on graph theory. This research finds that there is a trend in the users' behavior over time though product adjacency fluctuates over time. The system is tested on its usability. The tests show that implementing this recommendation system increases users' intention to purchase and reduces the search time.

• Journal of Korea Multimedia Society
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• v.18 no.6
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• pp.734-741
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• 2015

Coating is a type of paint. It protects a product forming a film layer on the product and assigns various properties to the product. Coating is one of the fields which is being studied actively in the polymer industry. Importance of coating in various industries is more increased. However, mixing process has been performing in dependence on operator's experience. In this paper, we found the relationship between each data from coating formulation process. We propose a framework to analyze the coating formulation process as well. It can improve the coating formulation process. In particular, the suggested framework may reduce degradation and loss costs due to absence of standard data which is accurate formulation criteria. Also it suggests responses to errors which can be occurred in the future through the analysis of the error data generated in mixing step.

• Journal of Information Technology Services
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• v.13 no.2
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• pp.133-149
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• 2014

It is unavoidable to provide products that meet customers' needs and wants so that firms may survive under the competition in this globalized market. This paper focuses on how to provide levels for attributes that compse product so that firms may give the best products to customers. In particular, its main issue is how to determine common attributes and the others with their appropriate levels to maximize firms' profits, and how to construct a decision support system to ease decision makers' decisons about optimal common attribute selection using the Semantic Web and SWCL technologies. Parameter data in problems and the relationships in the data are expressed in an ontology data model and a set of constraints by using the Semantic Web and SWCL technologies. They generate a quantitative decision making model through the automatic process in the proposed system, which is fed into the solver using the Logic-based Benders Decomposition method to obtain an optimal solution. The system finally provides the generated solution to the decision makers. This presentation suggests the opportunity of the integration of the proposed system with the broader structured data network and other decision making tools because of the easy data shareness, the standardized data structure and the ease of machine processing in the Semantic Web technology.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.1
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• pp.33-43
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• 2013

The research on data mining that can manage a large amount of information efficiently has grown with the drastic increment of information. Privacy-preserving data mining can protect the privacy of data owners. There are several privacy-preserving association rule, clustering and classification protocols. A privacy-preserving association rule protocol is used to find association rules among data, which is often used for marketing. In this paper, we propose a privacy-preserving k-bits inner product protocol based on Shamir's secret sharing.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2000.10a
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• pp.31-35
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• 2000

We worried about the technology difference between our company and the advanced company at present motor market and are asked to set up the independent coil insulation system to accumulate insulation technology data. And to export our products at oversee market, we are asked to the evaluation of insulation performance to show our product excellence. In this study, we evaluated the insulation system of our motor, and studied the insulation diagnosis technology systematically to do site diagnosis. We are now accumulating the measured data. And also to reduce the initial insulation failure, we performed the insulation characteristic test and acquired the data to evaluate the initial soundness. We are doing the improvement of the insulation system. And also these data were used to new product development as very useful data, also will be used in the insulation deterioration diagnosis to estimate the remained life time which is very important data for the maintenance management. As the result, we were able to get our product reliability.

• International Journal of CAD/CAM
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• v.7 no.1
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• pp.1-10
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• 2007

The compression of CAD models is a key technology for realizing Internet-based collaborative product development because big model sizes often prohibit us to achieve a rapid product information transmission. Although there exist some algorithms for compressing discrete CAD models, original precise CAD models are focused on in this paper. Here, the characteristics of hierarchical structures in CAD models and the distribution of their redundant data are exploited for developing a novel data encoding method. In the method, different encoding rules are applied to different types of data. Geometric data is a major concern for reducing model sizes. For geometric data, the control points of B-spline curves and surfaces are compressed with the second-order predictions in a local coordinate system. Based on analysis to the distortion induced by quantization, an efficient method for computation of the distortion is provided. The results indicate that the data size of CAD models can be decreased efficiently after compressed with the proposed method.

• Asia pacific journal of information systems
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• v.32 no.2
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• pp.226-248
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• 2022

The existing model for sentiment analysis of product reviews learned from past data and new data was labeled based on training. But new data was never used by the existing system for making a decision. The proposed Aspect-based multi-agent Deep Reinforcement learning Sentiment Analysis (ADRSA) model learned from its very first data without the help of any training dataset and labeled a sentence with aspect category and sentiment polarity. It keeps on learning from the new data and updates its knowledge for improving its intelligence. The decision of the proposed system changed over time based on the new data. So, the accuracy of the sentiment analysis using deep reinforcement learning was improved over supervised learning and unsupervised learning methods. Hence, the sentiments of premium customers on a particular site can be explored to other customers effectively. A dynamic environment with a strong knowledge base can help the system to remember the sentences and usage State Action Reward State Action (SARSA) algorithm with Bidirectional Encoder Representations from Transformers (BERT) model improved the performance of the proposed system in terms of accuracy when compared to the state of art methods.

• Journal of Distribution Science
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• v.13 no.5
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• pp.91-102
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• 2015

Purpose - This study aims to build a systematic frame for effective marketing performances by prioritizing product type and pertinent channel that are appropriate for digital channel characteristics. FCB grid model was used to define a product type, and Internet communication satisfaction index was considered as a marketing performance measuring tool for digital channel. Research design, data, and methodology - As systematic understanding for Digital marketing is still unfamiliar to even professional marketer, the hypothesis was established based on preliminary research by conducting a qualitative survey of marketing experts who already experienced digital marketing in the fields as well as existing related study literature. Through a preliminary research, the degree for understanding for digital marketing, current digital marketing (including product/channel mix) execution status, and difficulties for marketers who had experienced digital marketing were figured out. Based on preliminary research, the main part of survey was designed to examine which type of product would be effective for digital marketing and which digital channel would be effective to achieve marketing performance in line with marketing objectives. To collect data, the questionnaire survey was conducted for professional marketers who had experienced digital marketing in 10 different fields including FMCG, cosmetics, distribution industry for one month (July, 10, 2014~Aug, 10, 2014). A total of 90 questionnaire were distributed and 66 questionnaires were used for the analysis, excluding the unanswered and insincere questionnaires. The data were analysed using SPSS ver.18.0. Results - The analysis for product type which is pertinent to digital marketing and prioritization for digital channel per digital marketing performance type could be summarized as followings. First, high involvement buying decision type of product and rational purchasing decision type of product in FCB grid are more effective for digital marketing in terms of marketing performance. Therefore, marketers in field would prioritize considering product type before executing digital marketing. Second, factor for sales increase, potential consumer creation and brand awareness was represented respectively 31.25%, 21.9%, and 20.8% as a result of factor analysis in terms of digital marketing channel performance. Third, effective major digital channel per digital marketing performance factor was differently identified as each digital channel has its own peculiarity. For instance, search engine is more effective for increasing sales while social media such as facebook and Kakaotalk is more effective for encouraging consumer participation. Conclusions - As a result of this study, product type and peculiarity which were pertinently fit to digital marketing were identified by using FCB grid model, and also suggested framework for decision making of digital channel selection in line with marketing objectives for effective marketing performance. It also provided insight to professional marketer which type of product could be effective for digital marketing execution as well as which factors should be measured for digital marketing performance.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.615-616
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• 2006

Many manufacturing companies manage their production-related data for quality management and production management. Nevertheless, production related-data should be closely related to each other Stored data is mainly used to monitor their process and products' error. In this paper, we provide an enterprise-wide production data model for decision support system and product automation. Process data, quality-related data, and test data are integrated to identify the process inter or intra dependency, the yield forecasting, and the trend of process status. In addition, it helps the manufacturing decision support system to decide critical manufacturing problems.

• Archives of design research
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• v.12 no.4
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• pp.119-128
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• 1999

Product opportunity analysis in product planning is to analyze the feasibility for success over the detail product concept, and to grasp the new possible market based on exploring the trends of market and product itself. Therefore, the correct analysis and insight with various data of product and market is needed for product opportunity analysis. As product environment changes rapidly, it is especially important to collect more plentiful informations, and to put these information to practical use pertinently. It is consequently indispensible to clarify the types of information to be needed and to construct product database. However, there has no meaning to gather simple information which is lying here and there. Product database has to be systematically organized and each product information is to be transformed into contextual one. This study clarifies a conceptual framework of product design database based on product attributes and develops prototype of product database for product planning. Case study of camera is exemplified for analyzing the product trends and exploring product opportunity with developed product database.