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Amazon Product Queries and User Reviews
E-commerce & Online Transactions
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Free
About
This dataset contains product-related queries, item IDs, user IDs, original user ratings, and detailed reviews. It bridges the gap between user needs and product feedback, offering rich data for analysing customer preferences, sentiment, and product performance. This dataset is well-suited for building recommendation systems, sentiment analysis, and query-to-review mapping models.
Dataset Features:
- QID: Unique identifier for the query.
- Query: User's specific need or question regarding a product.
- Item_ID: Unique product identifier.
- User_ID: Unique identifier for the user submitting the review.
- Ori_Rating: Original star rating given by the user (1-5 scale).
- Ori_Review: Detailed review text provided by the user.
Usage:
The dataset is ideal for various natural language processing (NLP) and machine learning applications:
- Training and testing NLP models for sentiment analysis and product review summarisation.
- Developing personalised recommendation systems by matching user queries with product reviews and ratings.
- Query-to-review mapping for a better understanding of user needs and product effectiveness.
- Product feedback analysis to identify key features or improvements for consumer satisfaction.
Coverage:
This dataset spans multiple product categories, user preferences, and review sentiments, supporting diverse modelling approaches for e-commerce and customer experience analytics.
License:
CC0 (Public Domain)
Who can use it:
Data scientists, NLP practitioners, e-commerce analysts, researchers, and developers aim to enhance customer satisfaction, improve product insights, and build recommendation systems.
How to use it:
- Develop machine learning models for query matching and sentiment analysis.
- Use it for review summarization to extract key insights.
- Explore trends in user ratings and reviews for product development.
- Conduct textual analysis to understand customer preferences and concerns.
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