Microsoft patents AI model to predict group-level business conversions
Microsoft describes a machine learning method that combines data from user sequences, identity profiles, and conversion features to predict business outcomes. The system uses specific AI layers to process these inputs and generate a metric indicating whether a specific individual action leads to a broader group-level result.
In the filing’s own words
Modeled conversions for connection networking are described. A method comprises generating a first input vector comprising a set of sequence features for a group of entities using a transformer layer of a machine learning model, generating a second input vector comprising a set of identity profile features for the group of entities using a generative artificial intelligence layer, receiving a third input vector comprising a set of conversion features, concatenating the first input vector, the second input vector, and the third input vector into a concatenated vector, normalizing the concatenated vector to form a normalized vector, projecting the normalized vector to form a projected vector, and generating a first metric based on the projected vector using a multi-gate mixture-of-experts (MMOE) layer of the ML model, the first metric comprising a value indicating whether there is a deterministic entity level conversion event for a group level conversion event.
What exactly they claim (claim 1)
1. A method, comprising: generating a first input vector comprising a set of sequence features for a group of entities using a transformer layer of a machine learning (ML) model; compressing the first input vector to reduce a sequence length; generating a second input vector comprising a set of identity profile features for the group of entities using a generative artificial intelligence (GAI) layer of the ML model; receiving a third input vector comprising a set of conversion features; concatenating the first input vector, the second input vector, and the third input vector into a concatenated vector; normalizing the concatenated vector to form a normalized vector; projecting the normalized vector to form a projected vector; and generating a first metric based on the projected vector using a multi-gate mixture-of-experts (MMOE) layer of the ML model, the first metric comprising a value indicating whether there is a deterministic entity level conversion event for a group level conversion event.
Facts
- Company
- Microsoft (Microsoft Technology Licensing, LLC)
- Official title
- MODELED CONVERSIONS FOR A CONNECTION NETWORK SYSTEM
- Publication number
- US20260278339A1
- Application number
- 19079629
- Filed
- Mar 14, 2025
- Published
- Sep 17, 2026
- Inventors
- 6
- Claims
- 20
Classified under
G06N 3/0455 Physics & computingG06N 3/0475 Physics & computingMore from Microsoft in AI & software
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Summaries are simplified from the filing’s own abstract and first claim. A patent filing is not a product announcement.
Patent data and drawings: U.S. Patent and Trademark Office (USPTO). Nebula is not affiliated with or endorsed by the USPTO.