US 11,810,152 B2
Automatic item placement recommendations based on entity similarity
Xiang Chen, San Jose, CA (US); Viswanathan Swaminathan, Saratoga, CA (US); and Somdeb Sarkhel, San Jose, CA (US)
Assigned to Adobe Inc., San Jose, CA (US)
Filed by Adobe Inc., San Jose, CA (US)
Filed on Oct. 10, 2019, as Appl. No. 16/598,933.
Prior Publication US 2021/0110432 A1, Apr. 15, 2021
Int. Cl. G06Q 30/0251 (2023.01); G06F 16/28 (2019.01); G06F 16/22 (2019.01); G06Q 30/0241 (2023.01)
CPC G06Q 30/0254 (2013.01) [G06F 16/2237 (2019.01); G06F 16/2264 (2019.01); G06F 16/285 (2019.01); G06Q 30/0255 (2013.01); G06Q 30/0261 (2013.01); G06Q 30/0264 (2013.01); G06Q 30/0277 (2013.01)] 7 Claims
OG exemplary drawing
 
1. A system having an item placement configuration component to generate a recommended placement for a digital content item, the system comprising:
means for receiving a request for the recommended placement of the digital content item;
means for ascertaining an item type of the digital content item and an entity associated with the digital content item;
means for obtaining a multi-domain taxonomy for the item type, the multi-domain taxonomy describing how different entities relate to one another based on digital content items;
means for identifying a multi-dimensional vector that represents the entity within the multi-domain taxonomy, each dimension of the multi-dimensional vector corresponding to a grouping of digital content items and being quantified by a value indicating a degree of relevance between the entity and the grouping of digital content items;
means for identifying at least one of the different entities as being a similar entity by:
generating a mapping of the multi-domain taxonomy by embedding each of the different entities as a point in two-dimensional or three-dimensional space using a t-distributed stochastic neighbor embedding method; and
embedding the multi-dimensional vector into the mapping of the multi-domain taxonomy using the t-distributed stochastic neighbor embedding method; and
means for outputting a display of:
the recommended placement for the digital content item based on historic item placement configurations associated with the similar entity and independent of information specifying a cost threshold or an intended performance metric associated with placement of the digital content item;
an indication of the similar entity; and
at least one performance metric for the similar entity.