During my time at Alibaba Digital Agriculture, I was responsible for the Digital Rural Production and Marketing Docking Algorithm project.This project is a typical case of combining technology and agriculture to help the county achieve agricultural production and marketing docking through a data-driven approach.

# Project Background

The sales of agricultural products in counties face many challenges: asymmetric information, mismatch between supply and demand, high logistics costs, etc.Through data and technical means, we hope to help the county better match supply and demand, and improve the efficiency of agricultural product sales.

# Data base

We are based on huge amounts of data from Taos, including:

• • • Order data * *: Know which produce is popular and where demand is coming from
• • • Traffic data * *: Understand user search and browsing behavior
• • • Behavioral data * *: Understand user buying preferences and spending habits
• • • Portrait data * *: Understanding user attributes and spending power

# Algorithm model

We built several algorithmic models to support the business:

# # 1. Regional E-commerce Prediction Model

Forecast the demand for different types of agricultural products in different regions, and help the county to select suitable agricultural products for promotion.

# # 2. Category E-commerce Forecast Model

Predict the sales trends of different types of agricultural products at different times, and help the county to formulate sales strategies.

# # 3. Knowledge Graph

to build a knowledge map of agricultural products,