COMPLEMENTARY ITEM RECOMMENDATION SYSTEM

A recommendation system leverages multi-target search to provide item listing recommendations and/or query suggestions. For a given input image with multiple objects, multi-target search uses object detection to detect each object, and stores complementary object data associating each object from the image. Additionally, a search of an item listing datastore is performed using each object from the image as a search query. Based on item listings returned as search results, complementary item listings data associating item listings is stored. In some configurations, the complementary item listings data is also used to train a machine learning model to predict complementary item listings for a given item listing. When an input item listing is received, item listing recommendations and/or query suggestions are determined for the input item listing using the complementary object data, the complementary item listing data, and/or the machine learning model.