Sports coat category recommendation based on style characteristics
The diversified development of sports clothing styles brings diversified choices to consumers.In order to recommend clothing styles in line with consumers'preferences,the method of category recommendation based on style characteristics is put forward.The Analytic Hierarchy Process is used to determine the weight of attributes,and the key at-tribute factors are ranked to verify the importance of style attributes.Through data collection and modular division,the style parts are disassembled.After encoding the style features,a mathematical model based on vector representation is es-tablished.Combined with K-means clustering and BP neural network for identification and classification,it can effectively reduce the interference of human factors.The cosine similarity is used to calculate the similarity between clothing and cate-gory,and the recommendation is reasonable according to the data characteristics of clothing style and category.Similarity categories facilitate personalized recommendations based on consumer preference for clothing styles.
sport coatsstyle characteristicsattribute divisioncategory recommendationBP neural network
万方数据
维普
