• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.3
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• pp.91-101
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• 2011

Internet is becoming increasingly popular due to the rapid development of information and communication technology. There has been a convenient social activities such as the mutual exchange of information, e-commerce, internet banking, etc. through cyberspace on a computer. However, by using the convenience of the internet, the personal IDs(identity card, driving license, passport, student ID, etc.) represented by the electronic media are exposed on the internet frequently. Therefore, this study propose a feature extraction method to analyze the characteristics of image files containing personal information and a image retrieval method to find the images using the extracted features. The proposed method selects the feature information from color, texture, and shape of the images, and the images as searched by similarity analysis between feature information. The result which it experiments from the image which it acquires from the web-based image DB and correct image retrieval rate is 89%, the computing time per frame is 0.17 seconds. The proposed method can be efficiently apply a system to search the image files containing personal information and to determine the criteria of exposure of personal information.

• Journal of Arbitration Studies
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• v.21 no.2
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• pp.47-64
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• 2011

The China International Economic and Trade Arbitration Commission(CIETAC) released online arbitration rules which apply the resolution of disputes over electronic commerce transactions, as well as other economic and trade disputes in which the parties agree to do. The evidence submitted by the parties may be electronic evidence created, sent, received or stored by electronic, optical or magnetic means. Electronic evidence with a reliable electronic signature shall carry the same effect and probative force as a document with a hand-written signature. Where a case is tried in a tribunal, the arbitration tribunal shall conduct an online trial hearing using internet video conference or other electronic or computer communication means. Unless the parties have another agreement, summary procedure shall apply to cases where the amount in dispute exceeds RMB 100,000 but no more than RMB 1 million, or where the amount in dispute exceeds RMB 1 million and a party submits a written application for summary procedure after obtaining the written consent of the other party. Unless the parties have agreed otherwise, fast-track procedure shall apply to cases where the amount in dispute does not exceed RMB 100,000 or where the amount in dispute exceeds RMB 100,000 and a party submits a written application for fast-track procedure after obtaining the written consent of the other party. Notable features of the Online Rules are as follows; first, there is not detailed consideration for online arbitration. Second, communications between the parties and the tribunal are allowed only through the Secretariat. Third, elaborate provisions regarding the electronic submission and transmission of documents is provided for. Forth, various factors must be considered by the tribunal in deciding the evidence's reliability. Fifth, reasonable endeavours is levied on CIETAC to keep data communications secure and encrypted. Sixth, the tribunal has the right to investigate and collect relevant evidence. And finally different procedures are provided for in consideration of the various types of E-commerce.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.6
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• pp.255-264
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• 2016

Due to the development of information and communication technology, the great change on economics has grown and the biggest change is the e-commerce. With the methods of electronic financial frauds becoming advanced, reported phishing incidents have greatly increased. The Fraud Detection System(hereafter FDS) has taken effect to prevent electronic financial frauds, but economic losses still occurring. This Paper aims to analyze the financial environment, financial information technology environment, financial information technology security environment and some features of the institutional changes. In order to supplement the defect of FDS, it gives some recommendations for the improvement of the effective FDS Management System and information sharing on frauds with some public institution and a major consideration for collection or utilization of personal information.

• Journal of Internet Computing and Services
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• v.6 no.5
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• pp.111-121
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• 2005

As the scale of e-commerce has been increasing, information about products and service become diversified, Most current internet shopping mall. however, provides product information to consumers in collective arrangement. thus they devote a lot of efforts and time to select the product they want, In this paper, as providing consumers convenient interfaces adapting feature inquirer and parallel coordinate, a method for selecting a right product through searching the wanted products easily and comparing their features efficiently has been proposed. To evaluate the efficiency of the method proposed in this paper, several experiments to measure the time spent and the number of clicks of mouse taken in finding the product they want have been conducted. The results verify the effectiveness of the proposed method.

• International Journal of Advanced Culture Technology
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• v.8 no.3
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• pp.148-158
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• 2020

With the limited product information available in the m-shopping context, product-naming strategies affect consumer choices by expressing the key product features or the brand's images. Given the increasing dominance of the mobile commerce in consumption across various product categories, few studies have examined the role of product naming in consumer choices in the m-shopping. In filling the research gap, this study empirically analyzes the influence of the perceived diagnosticity of product names in m-shopping on consumer attitude towards the product. Moreover, the study tests the moderating influences of the individual characteristics of consumers (i.e., age, gender, and m-shopping experience) in the dynamics of the perceived diagnosticity impacting the product evaluations. The results of the study using an online survey reveal that the perceived diagnosticity of the product names significantly increases consumer attitude towards the product. Additionally, the moderating effects of gender, age, and m-shopping experience are all found significant: (1) The positive influence of the perceived diagnosticity of the product names is greater for males than for females. (2) The older the respondent, the more statistically significant the positive influence on diagnosticity. (3) The more respondents having m-shopping experience, the more positive the impact of the diagnosticity. Implications and limitations of the study are discussed.

• Journal of Information Technology Services
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• v.22 no.1
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• pp.43-56
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• 2023

With the development of the e-commerce market, various types of products continue to be released. However, customers face an information overload problem in purchasing decision-making. Therefore, personalized recommendations have become an essential service in providing personalized products to customers. Recently, many studies on GCN-based recommender systems have been actively conducted. Such a methodology can address the limitation in disabling to effectively reflect the interaction between customer and product in the embedding process. However, previous studies mainly use implicit feedback data to conduct experiments. Although implicit feedback data improves the data scarcity problem, it cannot represent customers' preferences for specific products. Therefore, this study proposed a novel model combining explicit and implicit feedback to address such a limitation. This study treats the average ratings of customers and products as the features of customers and products and converts them into a high-dimensional feature vector. Then, this study combines ID embedding vectors and feature vectors in the embedding layer to learn the customer-product interaction effectively. To evaluate recommendation performance, this study used the MovieLens dataset to conduct various experiments. Experimental results showed the proposed model outperforms the state-of-the-art. Therefore, the proposed model in this study can provide an enhanced recommendation service for customers to address the information overload problem.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.5
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• pp.599-604
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• 2005

This paper presents fuzzy rules to predict diagnosis of Wisconsin breast cancer with minimized number of feature in put using the neural network with weighted fuzzy membership functions (NEWFM) and the non-overlap area distribution measurement method. NEWFM is capable of self-adapting weighted membership functions from the given the Wisconsin breast cancer clinical training data. n set of small, medium, and large weighted triangular membership functions in a hyperbox are used for representing n set of featured input. The membership functions are randomly distributed and weighted initially, and then their positions and weights are adjusted during learning. After learning, prediction rules are extracted directly from n set of enhanced bounded sums of n set of small, medium, and large weighted fuzzy membership functions. Then, the non-overlap area distribution measurement method is applied to select important features by deleting less important features. Two sets of prediction rules extracted from NEWFM using the selected 4 input features out of 9 features outperform to the current published results in number of set of rules, number of input features, and accuracy with 99.71%.

• Journal of the Korea Society of Computer and Information
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• v.20 no.3
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• pp.139-144
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• 2015

Recently, to satisfy the customer's requirements for glasses such as rating of glasses or choosing, glasses industry is supporting various types and tools for making one's appearance good. Among various forms of online shopping with the development of online shopping and the rapid growth of IT technology, the intense competition also more deepen. The strategies for differentiated marketing and features for competitiveness of businesses in the online and offline shopping areas are required that our marketing target be settled the glasses marketing by analyzing. In this research, we study the strategy for implementing a site for glasses to customizing a person not to distinguish whether the customer is older or younger etc. For the purpose of implementing a site for glasses, first, we suggest a differentiated methodology through analysis of glasses industry service and features of existential representative glasses sites. Through the activation of the marketing strategies, marketing in a glasses market is expected to be competitive.

• Fashion & Textile Research Journal
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• v.16 no.1
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• pp.79-90
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• 2014

With the development of modern society, not only have the Internet and e-commerce been progressed but they also made 'consumption patten' diverse. Despite the internet clothing market growth, there is critical a disadvantage, which is consumers is not able to wear the products presented via online pictures. Thus, pictures on the internet are the only information customers can get, which has caused consciousness on the importance of dealing with 'customer review'. In spite of the fact that 'customer review' has undeniably evolved to be one of customers' essential requisites, the research on this subject is very limited. Until now, the studies on the internet shopping consumers' behavior mostly has to do with the features of 'customer review' such as 'a sense of exaggeration', 'usability', 'duality', 'purity', 'professionalism', 'reliability', and the 'similarity', etc.) Therefore, this study categorizes the characteristics of online shopping reviews to 'the number of reviews', 'the article-length', 'the existence of photos', 'the rewards for reviews', 'the contents of the reviews' and 'the freshness of the reviews' and reviews the impact of an features of 'customers' reviews' affecting the internet shopping sales promotion. Moreover, it is to contribute to the marketing strategies of a shopping mall by analyzing consumers' 'purchasing satisfaction', 'the intention of repurchasing', and 'the factors of viral marketing'.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.109-125
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• 2019

As interest on intelligent search engines increases, various studies have been conducted to extract and utilize the features related to products intelligencely. In particular, when users search for goods in e-commerce search engines, the 'color' of a product is an important feature that describes the product. Therefore, it is necessary to deal with the synonyms of color terms in order to produce accurate results to user's color-related queries. Previous studies have suggested dictionary-based approach to process synonyms for color features. However, the dictionary-based approach has a limitation that it cannot handle unregistered color-related terms in user queries. In order to overcome the limitation of the conventional methods, this research proposes a model which extracts RGB values from an internet search engine in real time, and outputs similar color names based on designated color information. At first, a color term dictionary was constructed which includes color names and R, G, B values of each color from Korean color standard digital palette program and the Wikipedia color list for the basic color search. The dictionary has been made more robust by adding 138 color names converted from English color names to foreign words in Korean, and with corresponding RGB values. Therefore, the fininal color dictionary includes a total of 671 color names and corresponding RGB values. The method proposed in this research starts by searching for a specific color which a user searched for. Then, the presence of the searched color in the built-in color dictionary is checked. If there exists the color in the dictionary, the RGB values of the color in the dictioanry are used as reference values of the retrieved color. If the searched color does not exist in the dictionary, the top-5 Google image search results of the searched color are crawled and average RGB values are extracted in certain middle area of each image. To extract the RGB values in images, a variety of different ways was attempted since there are limits to simply obtain the average of the RGB values of the center area of images. As a result, clustering RGB values in image's certain area and making average value of the cluster with the highest density as the reference values showed the best performance. Based on the reference RGB values of the searched color, the RGB values of all the colors in the color dictionary constructed aforetime are compared. Then a color list is created with colors within the range of ${\pm}50$ for each R value, G value, and B value. Finally, using the Euclidean distance between the above results and the reference RGB values of the searched color, the color with the highest similarity from up to five colors becomes the final outcome. In order to evaluate the usefulness of the proposed method, we performed an experiment. In the experiment, 300 color names and corresponding color RGB values by the questionnaires were obtained. They are used to compare the RGB values obtained from four different methods including the proposed method. The average euclidean distance of CIE-Lab using our method was about 13.85, which showed a relatively low distance compared to 3088 for the case using synonym dictionary only and 30.38 for the case using the dictionary with Korean synonym website WordNet. The case which didn't use clustering method of the proposed method showed 13.88 of average euclidean distance, which implies the DBSCAN clustering of the proposed method can reduce the Euclidean distance. This research suggests a new color synonym processing method based on RGB values that combines the dictionary method with the real time synonym processing method for new color names. This method enables to get rid of the limit of the dictionary-based approach which is a conventional synonym processing method. This research can contribute to improve the intelligence of e-commerce search systems especially on the color searching feature.