Microsoft Corporation
Content item similarity detection

Last updated:

Abstract:

Techniques for efficiently detecting similarity among electronic content items are provided. A vector is generated for each of multiple content items and is used to assign its corresponding content item to a group among multiple groups. A set of content items that is assigned to a particular group of the plurality of groups is identified. For each pair of content items in the set, a similarity score is generated and used to determine whether to classify the pair as similar to each other. Similarity data is updated if to identify the pair if it is determined to classify the pair of content items as similar to each other. The similarity data associates a first content item with a second content item. The second content item is prevented from being presented to a particular user for a period of time after the first content item is presented to the particular user.

Status:
Grant
Type:

Utility

Filling date:

29 Nov 2018

Issue date:

24 Aug 2021