Adobe, Inc.

Wreetabrata Kar

Viswanathan Swaminathan

Somdeb Sarkhel

Sarathkrishna Swaminathan

This disclosure generally covers systems and methods that determine demographic labels for a user or a group of users by using digital inputs within a predictive model for demographic classification. In particular, the disclosed systems and methods use a unique combination of classification algorithms to determine demographic labels for users as a potential audience of digital content items. When applying the combination of classification algorithms, the disclosed systems and methods use a first classification algorithm to determine user-level-latent features for each user within a group of users based on demographic-label statistics associated with particular digital content items. The disclosed systems and methods then use the user-level-latent features and session-level features (from sessions of each user consuming the digital content items) as inputs in a second classification algorithm to determine a demographic label for each user within the group of users.

Validating a target audience using a combination of classification algorithms

The present disclosure is directed toward systems and methods for identifying user segments. In particular, the systems and methods described herein evaluate user session logs to gather media content consumption history information associated with a plurality of users. Additionally, the systems and methods described herein analyze items of media content to identify keywords, genres, and other attributes, and further represent the items of media content as vectors. The systems and methods follow an algorithm to group items of media content into clusters and, based on the clusters of media content, further group users of media content into user clusters (e.g., user segments).

User segment identification based on similarity in content consumption

Embodiments of the present invention relate to facilitating selection of video advertisements for presentation in association with a video. In embodiments, advertisement quality associated with various video advertisements is referenced. Generally, the advertisement quality indicates a probability a viewer will continue viewing a portion of a video following presentation of the video advertisement presented in association with the video. The advertisement quality associated with the video advertisements is used to select one or more video advertisements for presentation along with the video. An indication of the selected video advertisements can be provided for integration with the video to present to the viewer.

Selecting video advertisements based on advertisement quality

Embodiments of the present invention relate to facilitating determining video advertisement quality. In embodiments, video advertisement data associated with a video advertisement or presentation of the video advertisement in association with a video is referenced. Such video advertisement data can indicate, for example, an advertisement characteristic, a video characteristic, a video session characteristic, and/or a viewer characteristic. The video advertisement data can be used to determine an advertisement quality associated with the video advertisement. The advertisement quality generally indicates a probability a viewer will continue viewing a portion of the video following presentation of the video advertisement presented in association with the video.

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West Lafayette, IN, United States of America

Wreetabrata Kar