Open AccessBuilding of Visual Analysis System for Design of Youth Sports Shoe Products Based on Comment Mining
Author(s) -
Shengbo Qian,
Kaixin Zhang
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1684/1/012019
Subject(s) - preprocessor , computer science , visualization , web crawler , data pre processing , key (lock) , big data , process (computing) , data collection , sentiment analysis , product design , data science , data mining , product (mathematics) , industrial engineering , engineering , artificial intelligence , world wide web , computer security , mathematics , operating system , statistics , geometry
This paper proposes a visual analysis system for data collection, pre-preprocessing and sentiment analysis to support whole-process innovative design of youth sports shoes. This system aims to analyze the sales data of sports shoe e-commerce sellers before and after design, provide reference for key design elements in innovative design of sports shoes based on 3D printing and realize dynamic closed design of pre-design data investigation and analysis and post-design feedback data analysis. With dynamic data collection technology based on a crawler, product feature extraction model, sentiment analysis model and big data visualization technology, this system can better satisfy data analysis requirement for innovative design of sports shoes.