US 11,860,941 B2
Outcome analysis for graph generation
Jennifer Kloke, Austin, TX (US); and Harlan Sexton, Palo Alto, CA (US)
Assigned to SymphonyAI Sensa LLC, Palo Alto, CA (US)
Filed by Ayasdi AI LLC, Redwood City, CA (US)
Filed on Mar. 29, 2022, as Appl. No. 17/657,121.
Application 17/657,121 is a continuation of application No. 16/438,453, filed on Jun. 11, 2019, granted, now 11,288,316.
Application 16/438,453 is a continuation of application No. 15/166,207, filed on May 26, 2016, granted, now 10,318,584, issued on Jun. 11, 2019.
Claims priority of provisional application 62/166,439, filed on May 26, 2015.
Prior Publication US 2022/0292138 A1, Sep. 15, 2022
This patent is subject to a terminal disclaimer.
Int. Cl. G06F 16/901 (2019.01)
CPC G06F 16/9024 (2019.01) 21 Claims
OG exemplary drawing
 
1. A non-transitory computer readable medium including executable instructions, the instructions being executable by a processor to perform a method, the method comprising:
receiving a data set;
for each metric of a set of metrics:
generating topological representations using the data set, each topological representation being generated using a metric-lens combination, at least one metric of the metric-lens combination being from the set of metrics, each topological representation including a plurality of nodes, each of the plurality of nodes having one or more data points from the data set as members, at least two nodes of the plurality of nodes being connected by an edge if the at least two nodes share at least one data point from the data set as members;
associating each node with at least one shared characteristic based, at least in part, on at least some of member data points of that particular node sharing the shared characteristic;
identifying groups within each topological representation that include a subset of nodes of the plurality of nodes that share a same or similar shared characteristics;
scoring each group within each topological representation based, at least in part, on entropy, to generate a group score for each group;
scoring each topological representation based on the group scores of each group of that particular topological representation to generate a graph score for each topological representation; and
providing an indication of at least one particular metric-lens combination associated with at least one topological representation based on the graph scores to enable justification and reproducibility of the at least one particular metric-lens combination associated with the at least one topological representation being indicated.