Recommending, as the name suggests, recommends products that can meet users’. Demands and needs according to users’ preferences and behaviors, so as to achieve the purpose of users’ purchase. In a broad sense, all product information that is actively. Pushed to users can be regarded as the category of recommendation. And the product recommendation with commercial monetization capability is also called advertisement. The management of advertisements is generally handled by a separate advertisement system, and the recommendation described below mainly refers to the recommended content of products other than advertisements.

1. Recommended basic information

The recommendation system is fundamentally to solve the problem of decision-making in marketing product selection, and all need to have some indicators to measure and evaluate the effect to provide the basis for the subsequent adjustment of the parameters of the recommendation strategy and optimization of the method. Common recommendation system metrics Albania Phone Number and search comparisons include precision, recall, and novelty.

The “evolution” of recommendation strategies

Albania Phone Number
Albania Phone Number

Determining the products that users like to recommend is to establish the relationship between people and products. All the above mentioned metadata needs to be associated according to the recommendation strategy. The development of recommended strategies has been extended from simple probabilistic analysis to the now more popular deep learning. We mentioned that the core of recommendation is to establish a relationship between people and products. Those who are close to each other are considered to be more relevant, and those who are farther away are considered to be less relevant.

The relationship between people and commodities also includes the relationship between people and people, commodities and commodities, thereby constructing a relationship graph. For example, the user portrait we often say is the basic data for setting the relationship between people. According to people and commodities, we can establish a two-dimensional coordinate.

According to the distance of the coordinates, the degree of relevancy is judged and the recommended product information is generated. Since the recommendation system has higher requirements on the algorithm than the general e-commerce business system, here we will introduce some situations of the recommendation strategy and algorithm from the product dimension. If you want to learn more about some algorithms, you can study them yourself.

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