Abstract: A method for allocating perishable products based on machine learning, includes using a sales estimation model to evaluate estimated sales of a plurality of perishable products in a predetermined period, using a rating model to calculate a predetermined rate of the plurality of perishable products in the predetermined period according to the estimated sales, using an allocation model to adjust an allocation ratio of the plurality of perishable products in a plurality of marketing channels according to the estimated sales and the predetermined rate if a current rate is lower than the predetermined rate, and determining the numbers of perishable products allocated to the plurality of marketing channels according to the allocation ratio.

Abstract: A rate adjustment method includes a rate estimation model generating a plurality of estimated rates according to a plurality of training data, a revenue estimation model generating an estimated revenue according to the plurality of estimated rates, updating the rate estimation model according to the estimated revenue to generate an updated rate estimation model, and inputting a plurality of current data into the updated rate estimation model to update the plurality of estimated rates.

Abstract: A method for retrieving data on a web page includes performing a simulated user operation on a target web page to generate a result web page, retrieving a source code of the result web page, creating a data table according to the source code, and performing a data cleaning operation with the data table to generate cleaned data and store the cleaned data in a database. Each temporary row of the data table is corresponding to a quotation plan.