Retail Product comparison Architecture using different AI/ML/NLP techniques

There are different ways in which we can compare the products in market. But we ultimately end up in some challenges or less accuracy in reaching the target details.

To overcome these challenges, we could go for cascading approaches which is one of the good approaches.

Below approaches can be followed in a cascading approach manner.

1. Title Similarity detection of different products

2. Image Similarity detection of different products

3. Attribute extraction/detection of different products

4. Price comparison of different products

Once the similarity is detected using the above approaches get the probability if the products are matching or not matching.

TITLE SIMILARITY MODEL:

IMAGE SIMILARITY MODEL:

DESCRIPTION/ATTRIBUTE EXTRACTION MODEL:

The above architecture can be used to compare the titles description but if we need to compare the features inside the product titles in different websites or link, we should go for NLP techniques to extract (using OCR) and then compare using Regex or NLP techniques. Price is also one of the feature that can be extracted and compared using the same technique.

Originally published on Medium