US 12,088,472 B2
System and method of managing events of temporal data
Manjunath Shantappa Sangashetty, Bengaluru (IN); Jyothi Rupa Sugavaneswaran, Bengaluru (IN); Nisha Parameswaran Kurur, Trivandrum (IN); and Ranjith Mohanakumaran Nair, Thiruvananthapuram (IN)
Assigned to UST Global (Singapore) Pte. Limited, Singapore (SG)
Filed by UST Global (Singapore) Pte. Limited, Singapore (SG)
Filed on Aug. 22, 2022, as Appl. No. 17/821,329.
Claims priority of application No. 202211022800 (IN), filed on Apr. 18, 2022.
Prior Publication US 2023/0336434 A1, Oct. 19, 2023
Int. Cl. H04L 41/147 (2022.01); H04L 43/0829 (2022.01); H04L 43/087 (2022.01)
CPC H04L 41/147 (2013.01) [H04L 43/0829 (2013.01); H04L 43/087 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method of managing events of temporal data, after receiving at least one current event, the method comprising:
receiving, a plurality of historical events related to temporal data;
selecting at least one predefined feature of interest from the plurality of historical events;
segregating the plurality of historical events into one or more buckets based on a time of occurrence of the plurality of historical events, using a sliding time window of a predefined size which is determined prior to receiving at least one current event;
determining at least one pattern based on the one or more buckets, using a pattern mining technique based on one or more predefined parameters, wherein the one or more predefined parameters comprises a maximum length of a rule, and wherein the maximum length is indicative of a maximum number of events involved in the rule; and
obtaining a set of predefined rules from the at least one pattern, wherein the set of predefined rules are obtained prior to receiving at least one current event;
receiving the at least one current event related to the temporal data;
identifying at least one predefined feature of interest of the at least one current event;
correlating the at least one current event with one or more clusters of events based on the at least one predefined feature of interest, in one of a real-time manner and a scheduled manner, wherein the one or more clusters are obtained by generating at least one of a similarity matrix and a distance matrix for the at least one current event by using at least one of a community detection technique and a clustering technique,
wherein correlating the at least one current event in the scheduled manner comprises:
segregating the at least one current event into one or more buckets based on a time of occurrence of the at least one current event, using the sliding time window of the predefined size which is determined prior to receiving the at least one current event;
determining whether the one or more clusters is present in each of the one or more buckets based on the set of predefined rules which are obtained prior to receiving the at least one current event; and
correlating the at least one current event based on the set of predefined rules which are obtained prior to receiving the at least one current event; and
wherein correlating the at least one current event in the real-time manner comprises:
identifying at least one rule from the set of predefined rules which are obtained prior to receiving the at least one current event, that matches with the at least one current event; and
correlating the at least current event with the one or more clusters based on the identified at least one rule.