• Journal of Intelligence and Information Systems
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• v.16 no.2
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• pp.1-17
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• 2010

Association rules among product items by association analysis suggest sales effect among products. These are useful for marketing strategies such as cross-selling and product display etc. However, if we evaluate more practical product values reflecting cross-selling effects, they will be also more useful for the decisions of companies such as product item selection for product assortment and profit maximization etc. This study proposes product value evaluation models with the concept of effective value based on single-item association chain and itemset association chain. In addition to that, we performed experiments with transaction data related to clothing of an online shopping mall in Korea to show the performances of our models. In result, we confirmed that some items increased in effective values compared with their pure values while the others decreased in effective values.

• Annual Conference on Human and Language Technology
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• 2022.10a
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• pp.571-575
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• 2022

본 논문에서는 통계청에서 매월 작성되는 온라인쇼핑동향조사를 위해, 언어모델 전이학습 기반 분류모델 학습 방법론을 이용하여, 관세청 제공 전자상거래 수입 목록통관 자료를 처리하기 위해서 해외 직접 구매 상품군 분류 모델을 구축한다. 최근에 텍스트 분류 태스크에서 많이 이용되는 BERT 기반의 언어모델을 이용하며 기존의 색인어 정보 분석 과정이나 사례사전 구축 등의 중간 단계 없이 해외 직접 판매 및 구매 상품군을 94%라는 높은 예측 정확도로 분류가 가능해짐을 알 수 있다.

• Journal of the Korean Home Economics Association
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• v.40 no.12
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• pp.63-83
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• 2002

본 연구는 미국 소비자들이 지각한 온라인 쇼핑속성에 대한 차원을 밝히고. 온라인 속성에 대한 중요성과 상품범주별 구매의도와의 관계를 밝혀 상품범주별 마케팅 전략과 인터넷 소비자 관리 및 교육 프로그램 개발에 기여하고자 하였다. 조사대상자는 가정에서 인터넷을 사용하고 있는 미국 소비자 303 명으로 구성되었으며, 질문지법에 의해 자료 수집되었다. 자료분석을 위해 탐색적 요인분석을 실행하였고, LISREL8에 의해 측정모델과 구조적 관계 모델을 동시에 검증하였다. 자료 분석결과를 요약하면 다음과 같다. 첫째, 소비자가 지각한 온라인 쇼핑에 대한 속성은 거래 및 비용, 사이트 디자인, 구매유인 프로그램, 상호 관계성의 4개 차원으로 분류되었다. 둘째, 온라인 상품은 구매의도에 따라 인지적 상품, 경험적 상품, 서비스 3개 범주로 분류되었다. 셋째, 지각된 온라인 쇼핑속성의 중요도와 각상품군 구매의도와의 구조적 관계모델을 추정한 결과,“거래 및 비용”은 3개의 상품군에 대한 구매의도에 모두 유의한 영향을 주었으며,“구매유인 프로그램”은 경험적 상품과 서비스에 대한 구매의도에 유의한 영향을 미쳤다. 따라서, 소비자들에게 중요하게 지각되는 인터넷 특정 속성 즉, 보완, 배달 및 비용을 초점으로한 상품범주별 차별화된 이점을 제시하여 효과적인 마케팅 전략을 수립해야 할 것이다. 또한, 전자 상거래와 관련 보완, 환불정책 등에 관한 소비자 교육과 보호법이 요구되고 있다.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.9
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• pp.363-372
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• 2019

A sequence refers to data in which the order exists on the two items, and purchase transaction data in which the products purchased by one customer are listed is one of the representative sequence data. In general, all goods have a product taxonomy, such as category/ sub-category/ sub-sub category, and if they are similar to each other, they are classified into the same category according to their characteristics. Therefore, in this paper, we not only consider the purchase order of products to compare two purchase transaction sequences, but also calculate their similarity by giving a higher score if they are in the same category in spite of their difference. Especially, in order to choose the best similarity measure that directly affects the calculation performance of the purchase transaction sequences, we have compared the performance of three representative similarity measures, the Levenshtein distance, dynamic time warping distance, and the Needleman-Wunsch similarity. We have extended the existing methods to take into account the product taxonomy. For conventional similarity measures, the comparison of goods in two sequences is calculated by simply assigning a value of 0 or 1 according to whether or not the product is matched. However, the proposed method is subdivided to have a value between 0 and 1 using the product taxonomy tree to give a different degree of relevance between the two products, even if they are different products. Through experiments, we have confirmed that the proposed method was measured the similarity more accurately than the previous method. Furthermore, we have confirmed that dynamic time warping distance was the most suitable measure because it considered the degree of association of the product in the sequence and showed good performance for two sequences with different lengths.

• 한국데이터정보과학회:학술대회논문집
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• 2001.10a
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• pp.12-12
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• 2001

정보기술을 바탕으로 전자상거래의 규모는 빠르게 늘어가고 있다. 본 연구에서는 종합쇼핑몰의 성격을 띠는 사이버 쇼핑몰의 고객과 구매 고객의 특성 등을 살펴보고 의사결정나무를 이용한 이탈고객의 분류, 쇼핑몰에 등록된 상품군과 인구특성적인 변수들간의 대응분석을 실시하여 쇼핑몰에 대한 인식을 제고한다.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.42 no.3
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• pp.357-366
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• 1997

Rice quality is considered to have two general meanings; 1) milling, cooking, and processing quality, which refer to suitability of the grain for a particular end-use; and 2) physical quality, which means cleanliness, soundness, and freedom from foreign materials. Grain type is associated with specific milling, cooking, and processing characteristics. Thus, this experiment was conducted to classify the grain type categories and marketing grades for Korean leading rice varieties. Length: width ratio of brown rice kernel ranged from 1.57 to 2.25 and most of varieties belonged to short grain except Tongil type rice varieties. Mean of length: width ratio of brown rice kernel was 1.77 and coefficient of variance was 4.79％ in short grain type varieties. Grain shape could be further classified into 5 types by length:width ratio of brown rice kernel; 1 type(less than 1.75), 2 type(1.76∼1.80), 3 type(1.81∼1.90), 4 type(1.91∼2.00), and 5 type (greater than 2.00). For 1 and 2 type of varieties, woven wire sieve having 1.7mm openings showed better whole-kernel yields for special marketing grade, and sieve having 2.0mm openings for 3 and 4 type of varieties. Grain type which classified into 5 categories was not associated with physicochemical and cooking characteristics of rice grain, but sensory evaluation of cooked rice showed better score for 1 type varieties in terms of appearance, gloss, flavor, texture, stickiness, and taste.

• Journal of the Korean Society of Clothing and Textiles
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• v.32 no.12
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• pp.1950-1962
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• 2008

Today the importance of color image is increasing for the brands as well as the products. This study was performed to classily the color image of baby's wear brands and to suggest how the color is effectively planned for the image. In order to classify the color image of 7 baby's wear brands, color palettes of 7 brands were also made by 6 subgroups, each season(summer, fall) by gender(boy, girl, new-born) and based on manufactured garments which were collected by on-line shops. Questionaries were organized with 40 pieces of the color palettes prints for 6 subgroups by 7 brands and 20 baby's wear image adjectives. The total 320 copies were used in the survey to students majored in fashion design. Questionaries were analyzed by factor analysis from SPSS 12.0 package program. There are 4 main factors for the color images of baby's wear brands, 'liveliness', 'loveliness', 'chic', 'neatness'. Not hue, but tone is more important to express the characteristics of color images of baby's wear brands. Also white and black are importantly used for baby's wear. The consistency of the brand color image across gender and season is very important to identify and strengthen the color image of brand.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.57-78
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• 2020

With the development of the Internet, consumers have had an opportunity to check product information easily through E-Commerce. Product reviews used in the process of purchasing goods are based on user experience, allowing consumers to engage as producers of information as well as refer to information. This can be a way to increase the efficiency of purchasing decisions from the perspective of consumers, and from the seller's point of view, it can help develop products and strengthen their competitiveness. However, it takes a lot of time and effort to understand the overall assessment and assessment dimensions of the products that I think are important in reading the vast amount of product reviews offered by E-Commerce for the products consumers want to compare. This is because product reviews are unstructured information and it is difficult to read sentiment of reviews and assessment dimension immediately. For example, consumers who want to purchase a laptop would like to check the assessment of comparative products at each dimension, such as performance, weight, delivery, speed, and design. Therefore, in this paper, we would like to propose a method to automatically generate multi-dimensional product assessment scores in product reviews that we would like to compare. The methods presented in this study consist largely of two phases. One is the pre-preparation phase and the second is the individual product scoring phase. In the pre-preparation phase, a dimensioned classification model and a sentiment analysis model are created based on a review of the large category product group review. By combining word embedding and association analysis, the dimensioned classification model complements the limitation that word embedding methods for finding relevance between dimensions and words in existing studies see only the distance of words in sentences. Sentiment analysis models generate CNN models by organizing learning data tagged with positives and negatives on a phrase unit for accurate polarity detection. Through this, the individual product scoring phase applies the models pre-prepared for the phrase unit review. Multi-dimensional assessment scores can be obtained by aggregating them by assessment dimension according to the proportion of reviews organized like this, which are grouped among those that are judged to describe a specific dimension for each phrase. In the experiment of this paper, approximately 260,000 reviews of the large category product group are collected to form a dimensioned classification model and a sentiment analysis model. In addition, reviews of the laptops of S and L companies selling at E-Commerce are collected and used as experimental data, respectively. The dimensioned classification model classified individual product reviews broken down into phrases into six assessment dimensions and combined the existing word embedding method with an association analysis indicating frequency between words and dimensions. As a result of combining word embedding and association analysis, the accuracy of the model increased by 13.7%. The sentiment analysis models could be seen to closely analyze the assessment when they were taught in a phrase unit rather than in sentences. As a result, it was confirmed that the accuracy was 29.4% higher than the sentence-based model. Through this study, both sellers and consumers can expect efficient decision making in purchasing and product development, given that they can make multi-dimensional comparisons of products. In addition, text reviews, which are unstructured data, were transformed into objective values such as frequency and morpheme, and they were analysed together using word embedding and association analysis to improve the objectivity aspects of more precise multi-dimensional analysis and research. This will be an attractive analysis model in terms of not only enabling more effective service deployment during the evolving E-Commerce market and fierce competition, but also satisfying both customers.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2002.05a
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• pp.160-163
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• 2002

제품 구입시 구매욕구를 일으키는 요소는 제품 속에 내재되어 있는 형태와 색이다. 제품개발자는 제품디자인의 시발점으로 기초도형에 대한 연구가 필요하고 이러한 기초도형의 감성은 결국 구체적인 디자인 형태로 변환될 경우 상당한 기초자료로 제시할 수 있을 것이다. 또 체계화된 기초자료를 이용하여 소비자의 취향에 맞는 제품의 개발을 촉진시키고, 소비자 계층의 유형별 분류와 상품군의 세분화 작업을 가속화시켜 상품의 양적 생산에서 질적생산으로 전환시킬 수 있는 계기가 될 것이다. 본 연구에서는 이러한 목적을 가지고 제품요소의 기본이 되는 형태와 색상에 있어서 시각감성이 지역, 성별, 도형간에 어떠한 차이가 있는지를 살펴보고자 한다.

• Journal of Digital Convergence
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• v.10 no.5
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• pp.67-78
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• 2012

Recently, the interesting of customers in online auto insurance is rapidly increasing. The one of major reasons is economical benefit. offline auto insurance products as a service formed high price. However, online auto insurance relatively formed low price. Thanks to these characteristics of online auto insurance has gained great popularity. Therefore, in purchasing online auto insurance, consumers carefully buy products of auto insurance. In this study, we classified the $2{\times}2$ matrix (online preference group, economic pursuit group, convenience oriented group, and carefulness approach group) in online auto insurance consumers focusing on the perceived benefits and price acceptance. From an economic point of view of consumers around the perceived benefits and price acceptance, we analyzed the relationships among easy of use, usefulness, attitude, and purchase intention in automobile e-shopping mall. The results of this study will provide the useful implications for the planing CRM(customer relationship management) strategy for improving purchase intention of customers to online insurance companies.