US 11,972,251 B2
Continuous learning-based application related trade-off resolution and implementation
Janardan Misra, Bangalore (IN); Vikrant Kaulgud, Pune (IN); Adam Patten Burden, Singapore (SG); Sanjay Podder, Thane (IN); Narendranath Sukhavasi, Nizamabad (IN); and Nibedita Sarmah, Bangalore (IN)
Assigned to ACCENTURE GLOBAL SOLUTIONS LIMITED, Dublin (IE)
Filed by ACCENTURE GLOBAL SOLUTIONS LIMITED, Dublin (IE)
Filed on Apr. 21, 2021, as Appl. No. 17/236,841.
Claims priority of application No. 202011017756 (IN), filed on Apr. 25, 2020; and application No. 202011030399 (IN), filed on Jul. 16, 2020.
Prior Publication US 2021/0334090 A1, Oct. 28, 2021
Int. Cl. G06F 9/44 (2018.01); G06F 8/70 (2018.01); G06N 5/01 (2023.01); G06N 20/00 (2019.01)
CPC G06F 8/70 (2013.01) [G06N 5/01 (2023.01); G06N 20/00 (2019.01)] 8 Claims
OG exemplary drawing
 
1. A continuous learning-based application related trade-off resolution and implementation apparatus comprising:
at least one hardware processor;
an application feature matrix generator, executed by the at least one hardware processor, to
generate, based on a plurality of historical tradeoff instances, an application feature matrix;
an association rule generator, executed by the at least one hardware processor, to
generate, based on the application feature matrix, association rules for historical tradeoff instances of the plurality of historical tradeoff instances for which decisions are not known;
a decision tree generator, executed by the at least one hardware processor, to
generate, based on the application feature matrix, a decision tree for historical tradeoff instances of the plurality of historical tradeoff instances for which decisions are known;
a rule inducer, executed by the at least one hardware processor, to
induce, based on the generated association rules and the generated decision tree, decision rules;
a cold start controller, executed by the at least one hardware processor, to
apply default rules to a cold start scenario;
a rule refiner, executed by the at least one hardware processor, to
refine the decision rules and the default rules to generate refined rules;
a confidence level analyzer, executed by the at least one hardware processor, to
determine, for each of the refined rules, a confidence level;
a rule prioritizer, executed by the at least one hardware processor, to
prioritize, based on the determined confidence level, the refined rules;
a tradeoff resolver, executed by the at least one hardware processor, to
apply, in order of priority from the prioritization of the refined rules, a specified number of the refined rules to a new tradeoff instance, and
generate, based on the application of the specified number of the refined rules to the new tradeoff instance, a resolution associated with the new tradeoff instance; and
a tradeoff implementer, executed by the at least one hardware processor, to
implement, with respect to the new tradeoff instance, the resolution associated with the new tradeoff instance, wherein the resolution associated with the new tradeoff instance includes build versus buy options for a new application and implementing the resolution includes:
determining confidence levels associated with the build versus buy options for the resolution;
enabling automatic selection of one of the build versus buy options having a higher confidence level from the determined confidence levels,
wherein if the build option is selected,
building the application by selecting application programming interfaces (APIs) matching functional requirements of the application and integrating the APIs as per templatized design architecture, and
wherein if the buy option is selected,
automatically selecting a vendor for purchasing the application.