• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.151-166
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• 2020

A recommender system is a system that recommends products or services that best meet the preferences of each customer using statistical or machine learning techniques. Collaborative filtering (CF) is the most commonly used algorithm for implementing recommender systems. However, in most cases, it only uses purchase history or customer ratings, even though customers provide numerous other data that are available. E-commerce customers frequently use a search function to find the products in which they are interested among the vast array of products offered. Such search keyword data may be a very useful information source for modeling customer preferences. However, it is rarely used as a source of information for recommendation systems. In this paper, we propose a novel hybrid CF model based on the Doc2Vec algorithm using search keywords and purchase history data of online shopping mall customers. To validate the applicability of the proposed model, we empirically tested its performance using real-world online shopping mall data from Korea. As the number of recommended products increases, the recommendation performance of the proposed CF (or, hybrid CF based on the customer's search keywords) is improved. On the other hand, the performance of a conventional CF gradually decreased as the number of recommended products increased. As a result, we found that using search keyword data effectively represents customer preferences and might contribute to an improvement in conventional CF recommender systems.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.3
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• pp.189-199
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• 2009

The amount of information on the Web is explosively growing as the Internet gains in popularity. However, only a small portion of the information on the Web is truly relevant or useful to the user. Thus, offering suitable information according to user demand is an important subject in information retrieval. In e-commerce, the recommender system is essential to revitalize commercial transactions, raise user satisfaction and loyalty towards the information provider. The existing recommender systems are mostly based on user data collected at servers, so user data are dispersed over several servers. Therefore, web servers that lack sufficient user behavior data cannot easily infer user preferences. Also, if the user visits the server infrequently, it may be hard to reflect the dynamically changing user's interest. This paper proposes a novel personalization system analyzing the user preference based on web documents that are accessed by the user on a user device. The system also identifies non-content blocks appearing repeatedly in the dynamically generated web documents, and adds weight to the keywords extracted from the hyperlink sentence selected by the user. Therefore, the system establishes at an early stage recommendation strategies for the web server that has little user data. Also, user profiles are generated rapidly and more accurately by identifying the information blocks. In order to evaluate the proposed system, this study collected web data and purchase history from users who have current purchase activity. Then, we computed the similarity between purchase data and the user profile. We confirm the accuracy of the generated user profile since the web page containing the purchased item has higher correlation than other item pages.

• Journal of Distribution Science
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• v.13 no.7
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• pp.85-90
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• 2015

Purpose - Global trends play a part to change the structure of the fashion industry. In particular, companies attempting to conduct innovative marketing centering on such products as SPA brands are growing into global companies. SPA stands for "Specialty Store Retailer of Private Label Apparel", meaning its activities are fully integrated from manufacturing through sales, including material procurement design, product, distribution, inventory management, and final sales. For this reason, more understanding of individual corporate profitability is very sensitive to consumer's attitudinal changes. The effects that corporate marketing activities on customer lifetime value through brand attitude were analyzed based on a structural equation model. Rust suggested value equity, brand equity, and relationship equity as customer equity driver. The study examines Chinese consumer because China is the fastest growing fashion market in the world. Research design, data, and methodology - The survey targeted Chinese college student age 20s. Only respondents who had purchased SPA brands in the past year were included for this research. A total of 303, except for 47 missing data of 350 distributed questionnaires were included in this research. The questionnaire is consists of six part to measure value, brand, relationship equity, attitude toward brand, purchase intention and demographic characteristics. This research conducted exploratory factor analysis and reliability test. To verify research hypotheses, structural equation model test was conducted. As for customer equity, diversified models in consideration of the scope of acquisition data, a method of collection of data, influencing factor, and predictability were suggested based on a net present value model. However, the history of customer equity study is relatively short, and sufficient empirical analyses have not been conducted, so more integrated analysis is required. In this study, the concept of driver suggested by Rust was applied to figure out the effects that consumer's attitude has on customer equity. The customer equity driver suggested by them consists of brand equity, value equity, and relationship equity. Results - This study reveals that value equity and brand equity have a positive influence on relationship equity. And, relationship equity has a positive influence on purchase intention through brand attitude. However, value equity and brand equity do not influence on brand attitude. Conclusion - The results of this research generated following implications. First, SPA brands need to take advantage of their value equity such as perceived low price and up-to-date fashion style to attract Chinese young consumer. Second, strong brand equity promises dominants position in the competitive market. As Chinese fashion market grows rapidly, SPA brands can consider branding strategy such as flagship store and celebrity marketing enhancing brand image. Third, the core concept of customer equity strategy is to maintain a relationship with their expecting and existing customers. The relationship equity is built by brand equity and value equity. When SPA brands serves product and service meet with individual customers, customers have intimacy to the brands.

• Journal of the Korea Society of Computer and Information
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• v.19 no.2
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• pp.193-200
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• 2014

Due to the advent of ubiquitous computing environment, it is becoming a part of our common life style. And tremendous information is cumulated rapidly. In these trends, it is becoming a very important technology to find out exact information in a large data to present users. Collaborative filtering is the method based on other users' preferences, can not only reflect exact attributes of user but also still has the problem of sparsity and scalability, though it has been practically used to improve these defects. In this paper, we propose clustering method by user's features based on SOM for predicting purchase pattern in u-Commerce. it is necessary for us to make the cluster with similarity by user's features to be able to reflect attributes of the customer information in order to find the items with same propensity in the cluster rapidly. The proposed makes the task of clustering to apply the variable of featured vector for the user's information and RFM factors based on purchase history data. To verify improved performance of proposing system, we make experiments with dataset collected in a cosmetic internet shopping mall.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.6
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• pp.253-260
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• 2015

When we buy items in online stores, it is common to face recommended items that meet our interest. These recommendation system help users not only to find out related items, but also find new things that may interest users. Recommendation system has been widely studied and various models has been suggested such as, collaborative filtering and content-based filtering. Though collaborative filtering shows good performance for predicting users preference, there are some conditions where collaborative filtering cannot be applied. Sparsity in user data causes problems in comparing users. Systems which are newly starting or companies having small number of users are also hard to apply collaborative filtering. Content-based filtering should be used to support this conditions, but content-based filtering has some drawbacks and weakness which are tendency of recommending similar items, and keeping history of a user makes recommendation simple and not able to follow up users preference changes. To overcome this drawbacks and limitations, we suggest weighted window assisted user history based recommendation system, which captures user's purchase patterns and applies them to window weight adjustment. The system is capable of following current preference of a user, removing useless recommendation and suggesting items which cannot be simply found by users. To examine the performance under user and data sparsity environment, we applied data from start-up trading company. Through the experiments, we evaluate the operation of the proposed recommendation system.

• Journal of Internet Computing and Services
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• v.24 no.5
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• pp.85-96
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• 2023

With advance of cloud computing technology, Blockchain as a Service of Cloud Service Provider has been utilized in various areas such as e-Commerce and financial companies to manage customer history and distribution history. However, if users' search history, purchase history, etc. are to be utilized in a BaaS in areas such as recommendation algorithms and search engine development, the users' search queries will be exposed to the company operating the BaaS, and privacy issues will be occured. Z. Guan et al. ensure the unlinkability between users' search query and search result using searchable encryption, and based on the inner product similarity, they select Top-k results that are highly relevant to the users' search query. However, there is a problem that the Top-k results selection may be not possible due to ties of inner product similarity, and BaaS over cloud is not considered. Therefore, this paper solve the problem of Z. Guan et al. using cosine similarity, so we improve accuracy of search result. And based on this, we design a BaaS with secure Top-k search that improved accuracy. Furthermore, we design a smart contracts that preserve privacy of users' search and obtain Top-k search results that are highly relevant to the users' search.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.29 no.3
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• pp.209-218
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• 2016

Recently, Wind-turbine electronic generator become popular. Wind-Turbine is free to cost for purchase and noise problem. For this reason, trend is shifting from Wind-turbine on land to offshore. Research and Development for offshore Wind-turbine has been conducted by various research institution. However, There is no solid design code for offshore Wind-turbine even in domestic as well as foreign. In this paper, conduct seismic analysis and compare results using design codes Korea Bridge Design Codes, Korea Harbor and Marina Design Codes, and DNV OS. Time-History analysis conducted for checking time dependent effect. The Added-Mass Method applied to consider water-structure effects and compared for w/ water and w/o water condition.

• Journal of Information Technology Applications and Management
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• v.22 no.1
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• pp.77-93
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• 2015

As the range of the customer choice becomes more diverse, the average life span of companies' products and services is becoming shorter. Most companies are striving to maximize the revenue by understanding the customer's needs and providing customized products and services. However, companies had to bear a significant burden, in terms of the time and cost involved in the process of determining each individual customer's needs. Therefore, an alternative method is employed that involves grouping the customers into different categories based on certain criteria and establishing a marketing strategy tailored for each group. In this way, customer segmentation and customer clustering are performed using demographic information and behavioral information. Demographic information included sex, age, income level, and etc., while behavioral information was usually identified indirectly through customers' purchase history and search history. However, there is a limitation regarding companies' customer behavioral information, because the information is usually obtained through the limited data provided by a customer on a company's website. This is because the pattern indicated when a customer accesses a particular site might not be representative of the general tendency of that customer. Therefore, in this study, rather than the pattern indicated through a particular site, a customer's interest is identified using that customer's access record pertaining to external news. Hence, by utilizing this method, we proposed a methodology to perform customer segmentation. In addition, by extracting the main issues through a topic analysis covering approximately 3,000 Internet news articles, the actual experiment applying customer segmentation is performed and the applicability of the proposed methodology is analyzed.

• Korean Journal of Social Welfare
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• v.39
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• pp.74-102
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• 1999

The integrated global economic system have intensed Liberalization, dereguration, privatization. National states were subordinated in global economic system. To save social costs and to encourage the national competition power, the globalized market tends to reduce the domestic social expention. Truely anxious things are not the defectiveness of capitalism itself but neo-liberal measures of each national states. So neo-liberal globalization beat welfare states. Welfare and growth, accumulation and justice are inter-conflict elements, and these confliction is well explained in context of globalization. Stratigies of growth pursuing economic benefits subordinate social policy in economic policy. Globalization did not always reduce the power of national state, but each national states purposely reduce the power of state and state participations. Thus Globalization can be overcome and must be overcome, eventually, the history of social welfare in korea differ frome that of European states. Their's social welfare retrenchment have based on the excessly expeneded welfare provision, but the frame of social welfare in korea is not yet established in history. Fundamentally historic experiences between European and korean social welfare are different. So "the third way" in korea must be in carefull approaches and the social welfare policy in korea must purchase "anti-market policy" and the equal distribution.

• International Journal of Computer Science & Network Security
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• v.23 no.2
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• pp.111-125
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• 2023

Due to the car's central role in modern life, the industry has become more fiercely competitive, with each manufacturer doing everything it can to attract buyers with features like plush interiors, comprehensive warranties, and helpful customer service departments. Customers may not have the luxury of buying a new car, so they will have to buy a used car. Nevertheless, in most cases, the customer (car driver) may be deceived about the vehicle information and history and thus will be confused in making his/her decision to purchase. In addition, after all attempts to obtain vehicle information (plate number, model, year of manufacture, number of maintenance times, accidents, etc.), the customer's many attempts may fail. In general, the government records and verifies the information of all cars, even those that pass through their borders. However, there might still be some trouble in obtaining this information. From this standpoint, we will design a website that makes it easier for car drivers, car companies and governments to carry out all the above-mentioned processes. It will also allow users, whether a driver or a car company, to inquire about all vehicle information through detailed and integrated reports on its condition since its entry into the Kingdom of Saudi Arabia until the present time, in addition to information supported by numbers and statistics to ensure the integrity and reliability of the information. This platform will save the trouble of searching for car information for drivers and car companies. It will also help governments keep track of the information of all cars entering and leaving the Kingdom of Saudi Arabia, which will contribute to facilitating the process of viewing the history of any car that has previously entered the Kingdom's borders.