Abstract: Described herein is a system and computer implemented method for finding similars for a selected clothing image amongst a set of clothing images in an electronic catalog in an online store serving online customers. An object detection model is applied to extract the clothing section within the clothing images to create a preprocessed image. A first machine learning model is applied on the preprocessed image(s) to convert the colors and textures of said preprocessed image into a first set of vector representations. A second machine learning model is applied on the preprocessed image(s) to convert the shapes of said preprocessed image into a second set of vector representations. Operations of mapping nearest vectors, matching attributes, sorting and ranking are performed, and thereafter similar images are displayed to the online customer.

Abstract: Described herein is a method by which more than one person is enabled to actively participate in the process of finalizing a real estate property either for purchase or rent. Each deciding party is enabled to create a custom style profile capturing their individual preferences at an attribute level by providing both visual and verbal feedback. A Collective Preferences Profile (CPP) is created by integrating the multiple style profiles of the chosen deciding parties. The generated CPP is then utilized to curate the different houses available and to surface those houses that are most likely to fit the aesthetic and requirements of the combined audience. The CPP evolves on an ongoing basis by active solicitation of feedback on properties viewed or waitlisted to accommodate changing preferences and provide the most suited recommendation at any time.