Abstract: The present embodiments provide visual search techniques which produces results that include both accurate similar items as well diversified items through attribute manipulation. In some embodiments, a feature vector describing the item of interest is obtained. A target feature vector is then generated at least partially from the original feature vector, in which the target feature vector shares only a subset of attribute values with the original feature vector and includes at least some values that are different from the original feature vector. An electronic catalog of items is then queried using the target feature vector, and a set of candidate items are determined from the electronic catalog based at least in part on similarity to the target feature vector. The original feature vector may be used to query for a set of similar items that are as similar as possible to the item of interest.

Abstract: Disclosed are various embodiments of systems and methods for dynamically generating and providing personalized recommendations of newer products or services potentially of interest to a particular user who has previously purchased a similar product or service. Historical purchase data or other information indicating the user's preferences is analyzed to determine personal preference data. Candidate content is identified based on attributes found in the preference data. Similarity strategies and criteria can be used to test features and qualities in candidate content. Recommended product or service content comes in the form of candidate content which reaches a similarity threshold or otherwise achieves a sufficient confidence score based at least in part on a similarity metric is determined.

Abstract: Various embodiments provide techniques for generating a style profile in which items are recognized in image data, analyzed for their attributes, and categorized based on those attributes. In various embodiments, computer vision techniques can be used to analyze the image data and subsequent image data to update the generated style profiles. The style profiles may be associated with a person, event, or the like and provide users with items having similar characteristics or attributes, which may be available for purchase in an electronic marketplace. The style profiles may be updated by analyzing user interaction with the provided items and by receiving additional image data. Additionally, recommendations may be provided based on search queries that identify certain events or style profiles.