• Gayatri Chaure
• Aishwarya Dani
• Vaishnavi Hapse
• Pradnya Jadhav
• Sharada Ohatkar

The potential uses of a technology are vast and continually expanding, as our knowledge and comprehension of it increases over time. An interesting and promising area that is currently being explored is the reverse image search. This technology has a wide range of applications that can greatly simplify our lives in various business sectors, as well as in our everyday routines. The way it works is by accepting images as the search input, rather than text, and returning similar images as the output, thereby making it easier for users to find what they are searching for. In this paper, the VGG16 model, which includes a combination of Convolutional Neural Networks (CNNs) and k-nearest neighbors (KNN) algorithm, is utilized to conduct reverse image searches. The results of the reverse image search are presented, and a short questionnaire is provided to the user to obtain feedback. The questionnaire inquiries about the product category, and the information gathered from the users’ responses is used to filter the relevant results by category.

Convolutional Neural Networks, k-nearest neighbors (KNN), reverse image search

"E-commerce recommendation system using reverse image search and questionnaire", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 5, page no.1044-1052, May 2023, Available :http://www.jetir.org/papers/JETIRFX06184.pdf

"E-commerce recommendation system using reverse image search and questionnaire", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 5, page no. pp1044-1052, May 2023, Available at : http://www.jetir.org/papers/JETIRFX06184.pdf