SYSTEM AND METHOD FOR DISCOVERING AND EXPLORING CONCEPTS AND ROOT CAUSES OF EVENTS

• US 20150032746A1
• Filed: 07/26/2013
• Published: 01/29/2015
• Est. Priority Date: 07/26/2013
• Status: Active Grant

• Current Assignee: Genesys Telecommunications Laboratories Incorporated (Genesys Cloud Services Incorporated)
• Original Assignee: Genesys Telecommunications Laboratories Incorporated (Genesys Cloud Services Incorporated)
• Inventors: Lev-Tov, Amir, Konig, Yochai, Faizakof, Avraham, Ollinger, David
• Granted Patent: US 10,061,822 B2
• Time in Patent Office: Days
• US Class Current: 707/737
• CPC Class Codes: G06F 16/243 Natural language query formulation
• CPC Class Codes: G06F 16/2465 Query processing support for facilitating data mining operations in structured databases
• CPC Class Codes: G10L 15/00 Speech recognition G10L17/00 takes precedence

Abstract

A method for determining a cause of events detected in a plurality of interactions includes: identifying, on a processor, a plurality of elements in the interactions; detecting, on the processor, a plurality of sequences of elements in the interactions; mining, on the processor, the plurality of sequences for generating a set of supported patterns; computing, on the processor, association rules from the set of supported patterns; and returning the computed association rules.

Claims

1. A method for determining a cause of events detected in a plurality of interactions, the method comprising:

identifying, on a processor, a plurality of elements in the interactions;

detecting, on the processor, a plurality of sequences of elements in the interactions;

mining, on the processor, the plurality of sequences for generating a set of supported patterns;

computing, on the processor, association rules from the set of supported patterns; and

returning the computed association rules.

2. The method of claim 1, wherein the elements comprise defined topics and identified concepts.

3. The method of claim 2, wherein the identified concepts are derived by:

filtering, on the processor, the interactions based on intervals;

creating, on the processor, a plurality of sentences from the filtered interactions;

computing, on the processor, a saliency of each the sentences;

pruning away, on the processor, sentences with low saliency for generating a set of informative sentences;

clustering, on the processor, the sentences of the set of informative sentences for generating a plurality of sentence clusters, each of the clusters corresponding to a concept of the concepts;

computing, on the processor, a saliency of each of the clusters; and

naming, on the processor, each of the clusters.

4. The method of claim 1, wherein the detecting the sequences of elements comprises:

sorting the identified elements in each interaction by timestamp within the interaction for generating the plurality of sequences; and

condensing each of the sequences for removing repeated consecutive elements.

5. The method of claim 1, further comprising condensing, on the processor, the set of supported patterns for removing repeated elements in the sequences.

6. The method of claim 1, wherein the computing the association rules from the set of condensed supported patterns comprises:

computing an association rule for each sequence pattern in the condensed supported patterns, the computing the association rule comprising, if the sequence pattern comprises more than one element;

dividing the sequence pattern into a first portion and a second portion, the second portion comprising the last element in the sequence pattern;

generating a proposed association rule, the proposed association rule being a logical implication from the first portion to the second portion;

computing a confidence of the proposed association rule;

if the computed confidence is greater than a threshold confidence level, storing the proposed association rule and moving the last element in the first portion to the second portion and iteratively repeating generating the proposed association rule and computing the confidence; and

if the computed confidence is less than a threshold confidence level, ending analysis of the sequence pattern and returning a previously stored proposed association rule as the association rule or returning no association rule if no such proposed association rules were stored.

7. The method of claim 6, further comprising computing a lift and a saliency of the association rule.

8. The method of claim 6, further comprising computing a lift and a saliency of the proposed association rule.

9. A method for determining a root cause of an event detected in a plurality of interactions, the method comprising:

receiving, on a processor, a query for the root cause of the event;

searching, on the processor, a plurality of association rules, each of the association rules comprising one or more first portion elements and one or more second portion elements, each of the association rules being a logical implication from the first portion to the second portion; and

returning, from the processor, one or more association rules matching the query, the second portion elements of each of the matching association rules comprising the event.

10. The method of claim 9, wherein each of the association rules has a corresponding confidence value,

wherein the query comprises a confidence threshold, and

wherein the returning the one or more association rules matching the query further comprises returning association rules matching the query that have confidence values exceeding the confidence threshold.

11. The method of claim 9, wherein each of the association rules has a corresponding lift value and a corresponding saliency value,

wherein the query comprises at least one of a lift threshold and a saliency threshold, and

wherein the returning the one or more association rules matching the query further comprises returning association rules matching the query that have lift values or saliency values exceeding the lift threshold or the saliency threshold.

12. A computer system comprising:

a processor; and

a memory, wherein the memory has stored thereon instructions that, when executed by the processor, causes the processor to compute association rules between events detected in a plurality of interactions by;

identifying a plurality of elements in the interactions;

detecting a plurality of sequences of elements in the interactions;

mining the plurality of sequences for generating a set of supported patterns;

computing association rules from the set of supported patterns; and

returning the computed association rules.

13. The computer system of claim 12, wherein the elements comprise defined topics and identified concepts.

14. The computer system of claim 13, wherein the identified concepts are derived by:

filtering, on the processor, the interactions based on intervals;

creating, on the processor, a plurality of sentences from the filtered interactions;

computing, on the processor, a saliency of each the sentences;

pruning away, on the processor, sentences with low saliency for generating a set of informative sentences;

clustering, on the processor, the sentences of the set of informative sentences for generating a plurality of sentence clusters, each of the clusters corresponding to a concept of the concepts;

computing, on the processor, a saliency of each of the clusters; and

naming, on the processor, each of the clusters.

15. The computer system of claim 12, wherein the processor is further configured to compute association rules between events detected in a plurality of interactions by:

sorting the identified elements in each interaction by timestamp within the interaction for generating the plurality of sequences; and

condensing each of the sequences for removing repeated consecutive elements.

16. The computer system of claim 12, wherein the processor is further configured to compute association rules between events detected in a plurality of interactions by condensing the set of supported patterns for removing repeated elements in the sequences.

17. The computer system of claim 12, wherein the computing the association rules from the set of condensed supported patterns comprises:

computing an association rule for each sequence pattern in the condensed supported patterns, the computing the association rule comprising, if the sequence pattern comprises more than one element;

dividing the sequence pattern into a first portion and a second portion, the second portion comprising the last element in the sequence pattern;

generating a proposed association rule, the proposed association rule being a logical implication from the first portion to the second portion;

computing a confidence of the proposed association rule;

if the computed confidence is greater than a threshold confidence level, storing the proposed association rule and moving the last element in the first portion to the second portion and iteratively repeating generating the proposed association rule and computing the confidence; and

if the computed confidence is less than a threshold confidence level, ending analysis of the sequence pattern and returning a previously stored proposed association rule as the association rule or returning no association rule if no such proposed association rules were stored.

18. The computer system of claim 17, wherein the computing the association rule further comprises computing a lift and a saliency of the association rule.

19. The computer system of claim 17, wherein the computing the association rule further comprises computing a lift and a saliency of the proposed association rule.

20. A computer system comprising:

a processor; and

a memory, wherein the memory has stored thereon instructions that, when executed by the processor, causes the processor to respond to a query for the root cause of an event by;

receiving the query for the root cause of the event;

searching a plurality of association rules, each of the association rules comprising one or more first portion elements and one or more second portion elements, each of the association rules being a logical implication from the first portion to the second portion; and

returning one or more association rules matching the query, the second portion elements of each of the matching association rules comprising the event.