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Description
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Feature Description
This project aims to categorize ecommerce products based on their text descriptions that is usually available on e-commerce sites like Amazon and Flipkart using NLP and Machine learning.
Use Case
Below are few use cases how the project can enhance and automate product categorization effectively:
- Automated Product Categorization
In e-commerce, products from vendors are often described with inconsistent naming conventions, incomplete tags, or in multiple languages. NLP and ML can automatically analyze the product descriptions, titles, and other metadata to classify products into predefined categories (e.g., electronics, apparel, home goods). - Detecting Misclassified Products
Products that have been incorrectly categorized by vendors may lead to poor search results and a frustrating shopping experience. An NLP-based system could scan existing product listings for potential misclassifications. - Handling Product Synonyms and Variations
Products may have multiple variations or synonyms that are difficult to categorize manually.NLP models can understand the contextual similarities between different terms and ensure that products are categorized consistently, despite variations in descriptions.
Benefits
Accurate and automated product categorization significantly improves the search and discovery experience for customers. With products consistently placed in the right categories and subcategories, users can find what they are looking for more quickly, reducing frustration.
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