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Data · dataset · 2023

Consumer purchase data set of Tiktok stores from January to June 2021

Listed in ScienceDB

The data is obtained in real time through the DY interface.

Description

The cosine similarity code can be compiled by python compilers such as python, thomny, etc. to calculate the similarity of consumers. The code uses networkx, numpy, matplotlib, etc. to calculate and visualizeThe data includes 10 types of consumer vectors of different scales, simulated online consumer vectors and their category division data, all in the csv file format.

The ID in the first column of consumer vector data represents the consumer serial number, and the 2-6 columns represent the consumer's purchase records for five kinds of goods: Bread, Instant Noodle, Dehydrated Beef, Speech Strip and Cracker. Each row represents a consumer vector

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Where it is published

Catalogue records · 1

Topics

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Audio 65%
Provenance · 1 source records, 11 field assertions
SourceKeyLast seenRaw
ScienceDB10.57760/sciencedb.j00133.002119 d agoJSON v1
FieldAssertionExtractorEvidence
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