US 12,411,862 B2
Systems and methods to search for digital twins
Si Wu, Beijing (CN); Xi Wang, Beijing (CN); and Chuantao Yin, Beijing (CN)
Assigned to ORANGE, Issy-les-Moulineaux (FR)
Appl. No. 18/716,222
Filed by ORANGE, Issy-les-Moulineaux (FR)
PCT Filed Nov. 14, 2022, PCT No. PCT/IB2022/000672
§ 371(c)(1), (2) Date Jun. 4, 2024,
PCT Pub. No. WO2023/105282, PCT Pub. Date Jun. 15, 2023.
Claims priority of application No. PCT/CN2021/136819 (WO), filed on Dec. 9, 2021.
Prior Publication US 2025/0013654 A1, Jan. 9, 2025
Int. Cl. G06F 16/24 (2019.01); G06F 16/245 (2019.01); G06F 16/248 (2019.01); G06N 3/08 (2023.01)
CPC G06F 16/248 (2019.01) [G06F 16/245 (2019.01); G06N 3/08 (2013.01)] 10 Claims
OG exemplary drawing
 
1. A computer-implemented method of searching for digital twins in a target dataset on a computerized platform, said target dataset comprising a graph in which the digital twins are the nodes and the relations between them are the edges, the method comprising:
receiving a search query comprising one or more search terms;
generating a semantic embedding of the search query;
comparing the semantic embedding of the search query with respective semantic embeddings generated in respect of each of a plurality of digital twins on said computerized platform, to determine a first set of one or more digital twins having semantic embeddings similar to the semantic embedding of the search query;
inputting, into a trained graph neural network, feature data of the first set of one or more digital twins and data from said graph, to generate at least one respective graph embedding in respect of the first set of digital twins, said trained graph neural network comprising a graph neural network architecture trained using training data from said graph;
comparing the at least one graph embedding generated by the trained graph neural network in respect of the first set of digital twins with graph embeddings generated by said trained graph neural network in respect of other digital twins on said computerized platform, to determine a second set of one or more digital twins whose graph embeddings are similar to the at least one graph embedding of said first set of digital twins; and
outputting search results comprising information identifying at least one digital twin of said second set of digital twins.