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With the rapid development of big data technology, many 'sleeping' data can be utilized, but the source of data is the key point. The previous methods of obtaining data can no longer meet the demand. This article uses python web crawler to down jacket of Alibaba International Station. Information (shell material, structure type, fill material, process information, and style information) is crawled and stored in the MongoDB database for data sources for apparel information analysis.

Keywords

Data Mining, Python Web Crawler, Clothing Information Analysis, Down Jacket.

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References

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Intelligent Recommendation System Based on K-means Clustering Algorithm

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Authors

Tang Zhi-hang ¹, Guo Tao ¹, Li Jun ¹, Wu Shi-qi ¹

Affiliations
1 School of Computer and Communication, Hunan Institute of Engineering Xiangtan 411104, CN

Source

International Journal of Advanced Networking and Applications, Vol 11, No 5 (2020), Pagination: 4393-4398

Abstract

Use python web crawler to collect data from Trade website. The collected data is down jacketinformation. The fields are shell material, structure type, filling material, process information and style information. This information can be used for data mining, using clustering algorithms, correlation algorithms, etc. to identify potential value, providing decision-making reference for the management of textile andgarment enterprises, with strong practical value. This paper provides a new idea for the development of textile and garment enterprises. The employees of the company screen, deal with the missing data and standardize thedata, and then conduct data mining. The management of the enterprise makes decisions based on the results of data mining to improve decision-making basis and correctness.

Keywords

K-Means Clustering Algorithm, Decision-Making, Intelligent Recommendation System.

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