US 11,960,520 B2
Hierarchical topic model with an interpretable topic hierarchy
Tanay Anand, Uttar Pradesh (IN); Sumit Bhatia, Uttar Pradesh (IN); Simra Shahid, Uttar Pradesh (IN); Nikitha Srikanth, Mysore (IN); and Nikaash Puri, Uttar Pradesh (IN)
Assigned to Adobe Inc., San Jose, CA (US)
Filed by Adobe Inc., San Jose, CA (US)
Filed on Jun. 29, 2022, as Appl. No. 17/853,141.
Prior Publication US 2024/0004912 A1, Jan. 4, 2024
Int. Cl. G06F 16/30 (2019.01); G06F 16/33 (2019.01); G06F 16/35 (2019.01); G06F 16/93 (2019.01); G06F 18/2133 (2023.01); G06F 18/2413 (2023.01); G06F 40/30 (2020.01)
CPC G06F 16/35 (2019.01) [G06F 16/3347 (2019.01); G06F 16/93 (2019.01); G06F 18/2133 (2023.01); G06F 18/24147 (2023.01); G06F 40/30 (2020.01)] 20 Claims
OG exemplary drawing
 
1. A method comprising:
determining first-level topics in a hierarchical topic model (HTM) related to a corpus of documents, wherein a first-level topic of the first-level topics comprises multiple words;
generating a number of clusters based on word embeddings of the multiple words;
subdividing the multiple words into second-level topics comprising subtopics of the first-level topic, wherein a number of the second-level topics is equal to the number of clusters;
assigning a document of the corpus of documents to the first-level topic and to a second-level topic of the second-level topics;
receiving an indication of access to the document at a client computing device; and
generating, using the HTM, custom content configured for the client computing device based on one or more other documents of the corpus of documents assigned to the first-level topic and the second-level topic.