introduction
For those who shop on Taobao, you may find a problem: Taobao often recommends sexy underwear on your homepage.Whether you have searched or purchased such products, they always appear in your recommendation list.Why is this?This article will explore this issue.
Taobao recommendation algorithm
Taobao is a huge e -commerce platform with a large amount of goods and a large number of buyers.How does its personalized recommendation system work?
Recommendation based on browsing records
Taobao’s recommendation system recommended products based on user browsing records.If you browse a lot of sexy underworld pages, the system will think you are interested in this product.Therefore, you will see more product -related product recommendations.
Based on buying history recommendation
If you once bought a sexy underwear on Taobao, the recommended system will first consider your purchase history, and recommend products with similar characteristics or similar brands.This is why you continue to receive relevant recommendations after you buy a sexy underwear.
Recommendation based on interest preferences
If you often browse fashion or beauty skin care products, Taobao will think that you are more concerned about fashion and beauty, so you may also see some recommended products related to sexy underwear.This is because sexy underwear is also a part of fashion and will be widely concerned.
Recommended based on similar products
When searching for sexy underwear on Taobao, the system will recommend similar or similar products based on your search history and other users’ purchase history.That’s why you searched for a sexy underwear, related products always appear in your recommendation list.
The impact of user behavior on recommendation
At the same time, your behavior will also affect the performance of the recommendation system.If you browse a lot of sexy underwear pages, but you do n’t buy it, the recommendation system will think that you are not interested in sexy underwear, and gradually reduce the recommendation of related products.
Criticism of Taobao recommendation algorithm
However, Taobao’s recommendation system is not perfect.Some people criticize that Taobao is too dependent on users’ browsing behaviors and ignores the understanding of the actual needs of users.Although Taobao’s recommendation algorithm is based on machine learning, simple statistical methods cannot completely capture the complexity of human purchase decision -making.
in conclusion
In short, Taobao’s recommendation algorithm is based on a comprehensive consideration of various factors, including browsing records, buying history, user interest preferences, and recommendation of similar products.Its purpose is to improve consumer shopping experience and help users quickly find products they are interested in.Although this algorithm is not perfect, it is an indispensable part of Taobao e -commerce ecosystem.
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