## 1 Introduction  
This paper compiles existing size data into a format that can be coded in a computer. Next, a customer personal size extraction function was developed on the Design U apparel web platform followed by the development of a coding system that providers can input actual size of the products. Finally, we presented the application of the technology to the shopping customer as an example of the recommended user interface that is a simple system as part of the shopping process. This study was conducted to solve the problems for customers who do not have expertise in clothing when choosing sizes. An important part of the study is to have more complete and varied body shape types of data. In addition, it is necessary to provide more precise size recommendations to customers by constantly upgrading more accurate numerical data. Furthermore, as the automatic size generation based on height and weight is often affected by the user's nationality, age, and body type, it is necessary to add more selection items for the relevant variables afterward. This is an increasing number of clothing shopping malls coinciding with the development of the internet. While customers used to wear and buy clothes in offline shops in the past, there are an increasing number of customers who buy clothes through online malls. Online shopping platforms offer the convenience of easy shopping for the consumers wherever they are, and fashion items are the fastest growing products [1]. Many factors, such as reliability, mind, suitability, and feelings/mood, affect customers when they select their clothes online [2]. Among them, the 'clothing fit' has been proven to be a crucial index for the consumers to evaluate the degree of satisfaction on all the clothes [3]. However, as customers have no professional knowledge on clothing, the size of clothing cannot be of great help. In an article in 2017, more than 16% of people answered that they could not select accurate size when they buy in an online shop. Therefore, it is useful to recommend suitable clothing sizes to the customer automatically [4; 5; 6; 7]. According to a study by [PERSON] (2018), the return rate of Chinese online clothing purchase was about 15% to 35% in which over 60% was associated with the clothing size [8]. For this purpose, it is necessary to collect and analyze customers' body size data and clothing size fit data for recommendations. Thus, research on the size-related data followed by development of an appropriate system is required. Data is often referred as a substantial volume of data that cannot be collected, stored, and analyzed by existing databases and many countries or companies are increasing their investment in it as they expect it will determine their future competitiveness. The current clothing industry in the era of data anticipates that a large body of customer data along with relevant clothing size data that varies with the seasons will be deemed as data and used for size recommendations, body type analysis, style recommendations, as well as product manufacturing in the future. This study collects and sorts out reference data for recommendation when customers input height, weight, and other body size variables. The scope of study sizes are women, men, and children. The size of men ranges from S-5 XL, the size of women ranges from 2 XS-3 XL and the size of children aged 1, 6, 9 months and 2-15 years of age. Compared with the customer numerical value, the actual size of clothing products is coded in terms of size coding when uploading the product. Therefore, it compares and recommends customer size on a real-time basis. The applied body sizes include three girth lengths and horizontal lengths. Therefore, the seller of clothing at a shopping mall can enter the tags in the shopping mall size coding system immediately and recommend the most appropriate size of ready-made clothing product to the customer through automatic comparison by the system.