# FIT5212 S1 2025 — Data

来源：https://www.kaggle.com/competitions/fit-5212-s-1-2025/data

本地 Meta Kaggle 快照；不是本次实时页面。

# Dataset Description

The data was collected by crawling the Amazon website and contains product metadata and review information about 219,859 different products. 
The user-item interaction data is the main data for this challenge. This data is further split into training and test sets. 
- train.csv. The training dataset contains a set of user_item ratings between users and items. The users explicitly rated the items that they interacted with between 1 to 5. 

- test.csv. Each user is provided with a list of items in the test dataset, for each user, you will need to predict the ratings for all the items in their list. 

The train dataset contains the following information:

- ID: an arbitrary ID for a row (does not contain any information)
- user_id: the id assigned to each user
- product_id: the id assigned to each product
- product_name: the name of the product
- rating: the explicit rating of a specific product_id by a user_id ranging from 1 to 5
- votes: the number of votes for a particular rating
- helpful_votes: the number of people that found the rating helpful

**Example**: The row below shows that the user with ID "1813" gave a rating of "5" to the product with ID "154533". The product is titled "Beautiful Thing". This rating received 10 votes, and 8 out of those 10 people found the rating helpful.
![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F7299706%2F8111d15a68ab02577dff212ab192ab21%2FScreenshot%202024-04-25%20at%206.36.25pm.png?generation=1714037271534359&alt=media)

The test dataset contains the following information:

- ID: an arbitrary ID for a row (does not contain any information). Avoid making any changes to this column as it is the main identifier when we mark your submission.
- user_id: the id assigned to each user
- product_id: the id assigned to each product
- product_name: the name of the product