• Akansha Pendharkar
• Pratiksha Sawalakhe
• Prasad Kumar Adhav
• Saurabh Singh

Online shopping forums are rapidly emerging and their popularity is growing significantly around the world. These forums rely heavily on search engines, which are primarily based on the knowledge base and use the same keywords to find similar products. However, customers want to set up an easy and reliable interaction in inquiring about related products. Offline shoppers face the problem of selecting products from a large number of online products available. The value of these products is growing significantly due to the large number of companies moving to online businesses. The user can assign, select, or click the image, and similar products based on the image will be introduced to the user. The proposed recommendation system is based on content-based image retrieval and is made up of two main categories; Phase 1 and Phase 2. In Phase 1, the proposed method reads the category/type of product. In Phase 2, the proposed recommendation system returns the closely related products and recommends the desired product to the user.

Recommendation system, Convolutional neural network, machine learning, collaborative Filtering, Content based Filtering

"Image Based Product RecommendationSystem", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 5, page no.i364-i366, May-2022, Available :http://www.jetir.org/papers/JETIR2205954.pdf

"Image Based Product RecommendationSystem", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 5, page no. ppi364-i366, May-2022, Available at : http://www.jetir.org/papers/JETIR2205954.pdf