US 12,346,361 B2
Hierarchical segmentation of unstructured text using neural networks
Inderjeet Nair, Ann Arbor, MI (US); Sumit Shekhar, Bengaluru (IN); Srikrishna Karanam, Bangalore (IN); Niyati Himanshu Chhaya, Hyderabad (IN); Natwar Modani, Bangalore (IN); Balaji Vasan Srinivasan, Bangalore (IN); and Aparna Garimella, Hyderabad (IN)
Assigned to Adobe Inc., San Jose, CA (US)
Filed by Adobe Inc., San Jose, CA (US)
Filed on Nov. 16, 2023, as Appl. No. 18/511,186.
Prior Publication US 2025/0165517 A1, May 22, 2025
Int. Cl. G06F 16/00 (2019.01); G06F 16/31 (2019.01); G06F 16/34 (2019.01)
CPC G06F 16/345 (2019.01) [G06F 16/322 (2019.01)] 20 Claims
OG exemplary drawing
 
1. A method comprising:
receiving unstructured text, the unstructured text including a sequence of sentences;
generating, by a neural network, a hierarchically segmented tree structure representing the unstructured text, the tree structure comprising tree structure nodes, wherein a leaf node of the tree structure nodes represents a sentence from the sequence of sentences;
determining segments and sub-segments of the unstructured text based on node data for the tree structure nodes of the hierarchically segmented tree structure; and
presenting for display a modified representation of the unstructured text based on the determined segments and sub-segments of the unstructured text.