Amazon Technologies, Inc.

Houssam Nassif

Vishwanathan Swaminathan

Sriram Srinivasan

Vijai Mohan

Yi Liu

Jian Liu

Tao Hu

Daniel Hill

Anand Mahadeva Iyer

Mitchell Howard Goodman

An optimal combination of content items may be determined and served to increase the likelihood of a predefined user interaction. A user can request content which may include an entity (such as a web page, document, advertisement, and the like) that has multiple components through which content items may be provided. For example, a web page may include multiple slots where content items may be displayed on the web page. Each component may be associated with multiple possible content items, resulting in many combinations of layouts for an entity. A content server may determine which layout to provide using a content selection model that is weighted based on a likelihood of groupings of content items resulting in a user interaction that satisfies a success condition (e.g., selecting a hyperlink, selecting a content item, initiating a transaction, etc.).

Artificial intelligence system for optimizing network-accessible content

The arrangement and selection of digital content to present to a user can be based upon criteria such as profitability or interest to a user. The selection can also be made to ensure that a diversity of item content is presented. The selection can utilize various rules or policies for diversity at the category level or item feature level, among other such options. In addition to selection diversity, the placement of item content displayed can satisfy various diversity criteria in order to ensure diversity of display as well.

Content selection algorithms

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Seattle, WA, United States of America

Houssam Nassif