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Publisher-based Assets

Overview

This dataset includes assets (images, text, and video) collected from a publisher’s page (url), and is useful for generating cookieless, contextual targeting solutions, as well as extracting raw assets to use in classification and categorization solutions.

Dataset

Field Type Description
publisher_id integer ID for the publisher that the asset payload is associated with.
page_id integer ID for the page that that asset was detected on.
type string Defines whether or not the asset is a text or image.
asset string For the text-based Asset type, this includes the text extracted from the page, which has been scrubbed of html and is designed to be machine readable. for the Image type, this field includes a URL to the source of the asset.
asset_alt_text string If type == “PublisherImageAsset” this will contain the descriptive alt text of the image, if found
asset_dimensions string If type == “PublisherImageAsset” this contains the actual dimensions of the asset (width x height)
asset_dimensions_on_page string regardless of the asset dimensions, what is the dimension of the asset as it appears on the publisher’s environment (image only) - note this defaults to 1280x1024 resolution
asset_percentage_of_viewport float The percentage of the active viewport does the asset comprise. (image assets only)
asset_viewability_by_resolution json a JSON blob of all the different viewability scores of the asset, depending on the client device resolution.
article_body string if the page type = “article” what is the refined and processed text of exclusively the article body. (text assets only.)
article_body_chars integer count of the characters included in the article_body. (text assets only.)
article_title string if page type = “article”, this is the title of the article. (text assets only.)
article_excerpt string if page type = “article” this is an excerpt of the article. (text assets only.)
asset_collection_date DateTime Timestamp for when the asset was collected.
classification json If the asset has been classified (via machine learning) the output will be included here. For both image and text-based assets, classification includes labeling, confidence scores, and brand safety data.