E-commerce Product Dataset

Project Overview

Objective

To establish a vast and varied dataset of e-commerce products, aiming to facilitate advancements in AI-driven e-commerce platforms, product recommendation systems, and inventory management solutions.

Scope

Compile images and metadata of a diverse range of e-commerce products across multiple categories and brands. Each product entry will have corresponding details like title, price, category, and customer reviews.

Sources

Collaboration with e-commerce platforms to access their product catalogs and images.
Data scraping from popular e-commerce websites, ensuring adherence to terms of use and data privacy regulations.
Partnering with small to medium e-commerce retailers for exclusive access to niche products.

Data Collection Metrics

Total Products: 1,000,000
Electronics: 200,000
Fashion & Apparel: 250,000
Home & Living: 150,000
Books & Stationery: 100,000
Others (Toys, Groceries, etc.): 300,000

Annotation Process

Stages

Metadata Compilation: Product details such as title, description, brand, and price are compiled.
Image Annotation: Relevant tags are assigned to product images to classify and describe them better.
Review & Validation: Industry experts review the collated data for accuracy and coherence.

Annotation Metrics

Total Annotated Images: 1,200,000 (Some products have multiple images)
Average Annotation Time per Product: 5 minutes

Quality Assurance

Automated Data Consistency Checks: Ensure product details don’t have discrepancies (e.g., an electronics item listed under the fashion category).

Image Verification: Use AI models to cross-verify that product images match their described categories and tags.

Expert Review: Products with high customer views or purchases are manually reviewed to ensure data accuracy.

QA Metrics:

Products Checked for Data Consistency: 600,000 (60% of total products)
Images Verified using AI Models: 720,000 (60% of total images)
Products Manually Reviewed: 50,000 (5% of total products)

Conclusion

The E-commerce Product Dataset is a pivotal resource for businesses aiming to integrate AI into their e-commerce platforms. By offering a comprehensive view of diverse products and their attributes, this dataset ensures better product recommendation, enhanced search functionalities, and improved customer experience on e-commerce platforms.