This page introduces and describes the capabilities of Vertex AI Search for the media industry. The page also provides links to more information, tutorials and checklists, to get you started with Vertex AI Search for media.
Vertex AI Search includes two capabilities specific for the media industry:
Media recommendations. Get recommendations for media content such as videos, news, and music. With media recommendations, audiences can discover more personalized content, like what to watch or read next, with Google-quality results customized using optimization objectives.
Media search. Get Google-quality search results with advanced query and document understanding designed for media content.
How media apps and generic apps differ
There are many similarities between media apps (and data stores) and generic apps (and data stores) in Vertex AI Search. However, there are some key feature differences:
Media apps use user events. You upload user events to personalize recommendations and rank search results for your audience.
Media apps require media metadata to conform to a predefined schema. This lets recommendations and search ranking use predefined, media-specific fields such as content ratings, aggregated ratings, persons, and production year to help generate results based on media engagement.
Media recommendations apps offer you a choice of models. Media recommendations apps let you choose what kind of recommendation to generate, such as recommending other content that users might like, similar items, or the most popular items.
Media recommendations apps offer you a choice of optimization objectives. For example, you can decide whether to optimize recommendations for click-through-rate to increase the number of interactions with content or conversion rate to increase the consumption of content.
The following table outlines some functional differences between media and generic data stores.
| Media apps and data stores | Generic apps and data stores |
|---|---|
| Data stores are always structured. | Data stores can be of any type (website, unstructured, structured). |
| Requires structured data with a predefined schema. | Schemas are optional for structured data. |
| You can create a data store only at the end of the app creation workflow. | You can create a data store independently of creating an app. |
| You can't create an app without connecting a data store to it. | You can create an app or a data store in any order and connect them later. |
| You must create and connect at least one data store at the end of the app creation workflow. You can create and connect multiple data stores to the app later. | You can create an app without any data store. |
| You can create empty data stores and add data to them later. | You cannot create an empty data store. You must import data into a data store during the data store creation process. |
| Data stores contain documents and user events. | Data stores contain documents only. |
| Imported historical user events are joined synchronously. | Imported historical user events are joined asynchronously. |
For more information, see About media data stores and documents and About apps and data stores.
Getting started tutorials
If you are new to Vertex AI Search, try out the getting started tutorials. These tutorials guide you step-by-step through the creation of an app. Data (documents and user events) are provided for the tutorials so all you need is a Google Cloud project and a billing account to create your first app:
Checklists
There is a lot of commonality between working with media apps and working with generic apps, but some features apply only to generic apps and other features only to media apps.
Use the following checklists to guide you through typical workflows specific to media: