Abstract: A method, system, and computer program product for discovering from user content, at least one tagged item that includes a product, includes identifying plural tags to be associated with each of the user-content item, and the corresponding probability that each of the plural tags is associated with products. There is also the feature of associating the plural tags and their corresponding probability of being associated with products. There are also the features of generating at least one subset of the tagged user content based upon the probability of a first one of the plural tags being associated with a product, and discovering the tagged user content comprising the product, from the subset of the tagged user content based upon the probability of the first one of the plural tags being associated with a product.

Abstract: A method, system, and computer program product generate at least one tagged image, and include the feature of determining at least one user content image from at least one subject image. There are also the features of identifying at least one product in the obtained user content image using at least one artificial intelligence model, and generating at least one tagged image with the identified product or products in the obtained user content image or images.

Abstract: A method, system, and computer program product generate at least one tagged image, and include the feature of determining at least one user content image from at least one subject image. There are also the features of identifying at least one product in the obtained user content image using at least one artificial intelligence model, and generating at least one tagged image with the identified product or products in the obtained user content image or images.

Abstract: A method, system, and computer program product for discovering from user content, at least one tagged item that includes a product, includes identifying plural tags to be associated with each of the user-content item, and the corresponding probability that each of the plural tags is associated with products. There is also the feature of associating the plural tags and their corresponding probability of being associated with products. There are also the features of generating at least one subset of the tagged user content based upon the probability of a first one of the plural tags being associated with a product, and discovering the tagged user content comprising the product, from the subset of the tagged user content based upon the probability of the first one of the plural tags being associated with a product.

Abstract: A method, system, and computer program product for dynamic content provisioning, such as for online marketing and product promotion, may include collecting user content from sources based upon collection parameters, and organizing the collected user content for optimization. There may also be the features of receiving rights-management data for the organized user content, and tagging the organized user content. Additionally, there may be receiving rights-management data for the organized user content, and generating an optimized display representation of tagged user content on an output interface for dynamic content provisioning.

Abstract: A method, system, and computer program product generate at least one tagged image, and include the feature of determining at least one user content image from at least one subject image. There are also the features of identifying at least one product in the obtained user content image using at least one artificial intelligence model, and generating at least one tagged image with the identified product or products in the obtained user content image or images.

Abstract: A method, system, and non-transitory computer-readable medium provides recommendations for a product, such as for online marketing. There is a method for providing recommendations for a product that includes receiving product rating service or other textual content from various sources. The method further includes matching at least one review information from the review information associated with plural reviews of the product. Additionally, there is filtering, sorting and searching the review information associated with plural reviews based on matching and one or more rating parameters. Further, the method includes publishing the filtered review information for the product in numerous gallery tile layouts. Also, the method includes generating a display representation of the published review information on an output interface for providing recommendations for the product.