US 12,293,156 B2
Deep technology innovation management by cross-pollinating innovations dataset
Raghavan Tinniyam Iyer, Bangalore (IN); Amod Deshpande, Pune (IN); Puneet Kalra, Pune (IN); Bhavna Butani, Gurgaon (IN); Kiran Raghunath Sathvik, Bangalore (IN); and Bhaskar Ghosh, Bangalore (IN)
Assigned to ACCENTURE GLOBAL SOLUTIONS LIMITED, Dublin (IE)
Filed by ACCENTURE GLOBAL SOLUTIONS LIMITED, Dublin (IE)
Filed on Aug. 10, 2022, as Appl. No. 17/885,423.
Prior Publication US 2024/0054290 A1, Feb. 15, 2024
Int. Cl. G06F 17/00 (2019.01); G06F 16/332 (2019.01); G06F 16/334 (2025.01); G06F 16/35 (2019.01); G06F 18/22 (2023.01); G06F 18/231 (2023.01); G06F 18/23213 (2023.01); G06F 40/284 (2020.01); G06F 40/295 (2020.01); G06F 40/30 (2020.01); G06N 5/022 (2023.01)
CPC G06F 40/30 (2020.01) [G06F 16/3326 (2019.01); G06F 16/3347 (2019.01); G06F 16/35 (2019.01); G06F 18/22 (2023.01); G06F 18/231 (2023.01); G06F 18/23213 (2023.01); G06F 40/284 (2020.01); G06F 40/295 (2020.01); G06N 5/022 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A system comprising:
a processor coupled to a memory, the memory storing instructions executable by the processor to:
extract a context-based keyword from an innovation dataset by transforming the innovation dataset to a vector, wherein the innovation dataset comprises data corresponding to an innovation;
search semantically relevant keywords for the extracted context-based keyword, by extracting an entity and a key phrase from the extracted a context based keyword, wherein the entities correspond to named entity recognition in the innovation dataset;
cluster the vector, by identifying frequent keywords in the semantically relevant keywords to obtain cluster centroids of the frequent keywords;
determine weighted keywords in each cluster using the obtained cluster centroids, and classify the weighted keywords to identify emerging innovation trends relevant to the innovation in the innovation dataset;
receive a two-layer user feedback from a user for the searched semantically relevant keywords, wherein the two-layer user feedback comprises a first layer of feedback corresponding to a relevancy of the searched semantically relevant keywords, and a second layer of feedback comprising an additional relevant keyword for each semantically relevant keyword; and
map the additional relevant keyword to the innovation dataset that comprises data corresponding to the innovation.