US 11,841,911 B2
Scalable retrieval system for suggesting textual content
Ji Li, San Jose, CA (US); Amit Srivastava, San Jose, CA (US); Adit Krishnan, Mountain View, CA (US); and Aman Malik, New Delhi (IN)
Assigned to Microsoft Technology Licensing, LLC, Redmond, WA (US)
Filed by Microsoft Technology Licensing, LLC, Redmond, WA (US)
Filed on Nov. 19, 2021, as Appl. No. 17/530,982.
Prior Publication US 2023/0161825 A1, May 25, 2023
Int. Cl. G06F 17/00 (2019.01); G06F 16/953 (2019.01); G06N 20/00 (2019.01)
CPC G06F 16/953 (2019.01) [G06N 20/00 (2019.01)] 20 Claims
OG exemplary drawing
 
1. A data processing system comprising:
a processor; and
a machine-readable storage medium storing executable instructions that, when executed, cause the processor to perform operations comprising:
receiving, from a client device, query text for a search query for a textual content recommendation, the query text comprising one or more words indicating a type of textual content items being sought;
providing the query text at an input to a first machine learning model;
analyzing the query text using the first machine learning model to obtain encoded query text, the first machine learning model being trained to identify features within the query text and to generate the encoded query text by mapping the features to a hyper-dimensional latent space (HDLS);
identifying one or more content items in a database of encoded content items that satisfy the search query, the features of the encoded content items being mapped to the HDLS, wherein identifying the one or more content items includes comparing attributes of the encoded query text with attributes of the encoded content items to identify content items that are closest to the encoded query text within the HDLS; and
causing the one or more content items to be presented on a display of the client device.