US 11,734,096 B2
Disaster prediction recovery: statistical content based filter for software as a service
Chethana Hebbal Basavarajappa, Bangalore (IN); Amita Ranjan, Bangalore (IN); and Kavya Reddy Musani, Austin, TX (US)
Assigned to VMWARE, INC., Palo Alto, CA (US)
Filed by VMWARE, INC., Palo Alto, CA (US)
Filed on Feb. 6, 2018, as Appl. No. 15/889,246.
Claims priority of application No. 201741037410 (IN), filed on Oct. 23, 2017.
Prior Publication US 2019/0122130 A1, Apr. 25, 2019
Int. Cl. G06F 11/00 (2006.01); G06F 11/07 (2006.01); G06N 5/047 (2023.01); G06F 11/22 (2006.01)
CPC G06F 11/079 (2013.01) [G06F 11/0706 (2013.01); G06F 11/0751 (2013.01); G06F 11/0778 (2013.01); G06F 11/0787 (2013.01); G06F 11/2263 (2013.01); G06N 5/047 (2013.01)] 15 Claims
OG exemplary drawing
 
1. A method to predict a disaster for a computer system based on logs, the method comprising:
representing existing logs as first vectors by tokenizing the existing logs;
partitioning the first vectors into clusters, the clusters representing disaster types;
selecting representative vectors for the clusters;
representing a new log of the computer system as a second vector by tokenizing the new log;
matching the second vector to a cluster by comparing the second vector and the representative vectors; and
categorizing the new log as a disaster type represented by the cluster,
wherein matching the second vector to the cluster by comparing the second vector and the representative vectors comprises:
computing similarity scores between the second vector and the representative vectors;
determining if a highest similarity score is greater than a threshold, the highest similarity score being between the second vector and a representative vector of the cluster;
wherein when the highest similarity score is not greater than the threshold:
computing additional similarity scores between the second vector and first vectors in the cluster; and
when an additional similarity score is greater than the threshold, concluding the second vector matches the cluster.