Deduplication using NLP

Question

I have a product catalog.

The user can add a new product to the catalog. The user can enter some attributes (such as color, weight, etc.) in the text boxes. The user can also mention the description of the product separately.

Each product will have a set of attributes explicitly mentioned by the user and a description. I want to check if there are any duplicate products in the catalog based on the attributes and descriptions provided by the user.

I want to perform the deduplication of records in the product catalog using the attributes and descriptions provided by the user.

Which NLP techniques can be used to perform the deduplication?

Answer 1

You could try the following:

1. Similarity Metrics: There are several similarity metrics that can be used to compare the similarity between two texts. For example, the Jaccard similarity coefficient, cosine similarity, and Levenshtein distance can be used to calculate the similarity between two product descriptions.

2. Named Entity Recognition (NER): NER is a technique used to identify and extract named entities (such as product names, brand names, etc.) from text. By using NER, we can identify if two products are referring to the same brand or product.

3. Topic Modeling: Topic modeling is a technique used to extract topics from a corpus of text. By applying topic modeling to the product descriptions, we can group similar products together based on their topics.