System and method for interactive multi-resolution topic detection and tracking

Patent metadata

Field	Value
Publication number	US-10061867-B2
Application number	US-201414586730-A
Country	US
Kind code	B2
Filing date	Dec 30, 2014
Priority date	Dec 30, 2014
Publication date	Aug 28, 2018
Grant date	Aug 28, 2018

Abstract

A method for tracking known topics in a plurality of interactions includes: extracting, by a processor, a plurality of fragments from the plurality of interactions; initializing, by the processor, a collection of tracked topics to an empty collection; computing, by the processor, a similarity between each fragment of the fragments and each of the known topics; and adding, by the processor, a known topic of the known topics to the tracked topics in response to the similarity between a fragment and the known topic exceeding a threshold value.

First claim

What is claimed is:

1. A method for tracking known topics in a plurality of interactions, the method comprising:
extracting, by a processor, a plurality of fragments from the plurality of interactions, the plurality of interactions occurring over a particular time period, each fragment of the plurality of fragments comprising one or more words;
initializing, by the processor, a collection of tracked topics to an empty collection;
computing, by the processor, a similarity between each fragment of the fragments and each of the known topics, each of the known topics comprising a template fragment comprising one or more template words, the similarity between a fragment of the fragments and a topic of the known topics being computed based on the one or more words of the fragment and the one or more template words of the template fragment of the topic;
adding, by the processor, a known topic of the known topics to the tracked topics in response to the similarity between a fragment and the known topic exceeding a threshold value; and
returning, by the processor, a collection of the tracked topics detected in the plurality of interactions, the collection comprising indications of frequencies at which the tracked topics occur in the plurality of interactions during the particular time period.

2. The method of claim 1 , wherein the known topics correspond to a first time period, and
wherein the interactions correspond to a second time period comprising the particular time period, the second time period being different from the first time period.

3. The method of claim 2 , further comprising:
receiving a time point from a user interface,
wherein the first time period is before the time point, and
wherein the second time period is after the time point.

4. The method of claim 1 , wherein the plurality of interactions correspond to a first time period comprising the particular time period, and
wherein the method further comprises:
extracting, by a processor, a second plurality of fragments from a second plurality of interactions, the second plurality of interactions corresponding to a second time period, the second time period being different from the first time period;
initializing, by the processor, a second collection of tracked topics to the empty collection;
computing, by the processor, a similarity between each fragment of the second fragments and each of the known topics; and
adding, by the processor, a known topic of the known topics to the second tracked topics in response to the similarity between a fragment and the known topic exceeding the threshold value.

5. The method of claim 4 , wherein the first time period has a length different from a length of the second time period.

6. The method of claim 4 , wherein the first time period has a start time different from a start time of the second time period.

7. The method of claim 1 , further comprising:
generating, by the processor, a visualization of the tracked topics.

8. The method of claim 7 , further comprising receiving, by the processor, a request to edit a topic of the tracked topics, the request comprising one or more of:
a request to change a color of the topic in the visualization;
a request to change a label of the topic; and
a request to remove fragments from the topic.

9. The method of claim 1 , further comprising:
receiving, by the processor, a user request to combine two topics of the tracked topics; and
merging, by the processor, the two topics of the tracked topics.

10. A method for detecting new topics in a plurality of interactions, given a plurality of known topics, the method comprising:
extracting, by a processor, a plurality of fragments from the plurality of interactions, the plurality of interactions occurring over a particular time period, each fragment of the plurality of fragments comprising one or more words;
initializing, by the processor, a collection of detected new fragments to an empty collection;
computing, by the processor, a similarity between each fragment and each of the known topics, each of the known topics comprising a template fragment comprising one or more template words, the similarity between a fragment of the fragments and a topic of the known topics being computed based on the one or more words of the fragment and the one or more template words of the template fragment of the topic;
identifying, by the processor, for each fragment, a corresponding topic having a highest similarity;
adding, by the processor, a fragment of the fragments to the collection of detected new fragments in response to the similarity between the fragment and the corresponding topic having the highest similarity is less than a threshold value;
extracting, by the processor, one or more new topics from the collection of detected new fragments; and
returning, by the processor, a collection of the one or more new topics detected in the plurality of interactions, the collection comprising indications of frequencies at which the one or more new topics occur in the plurality of interactions during the particular time period.

11. The method of claim 10 , further comprising:
receiving, by the processor, a request to stop tracking a blacklisted topic;
adding, by the processor, the blacklisted topic to a collection of blacklisted topics; and
computing, by the processor, a similarity between each fragment and each of the blacklisted topics,
wherein the computing, by the processor, the similarity between each fragment and each of the known topics is only performed in response to the similarity of the fragment to any blacklisted topic being less than a blacklist threshold value.

12. The method of claim 10 , further comprising:
receiving, by the processor, a request to start tracking a user topic;
adding, by the processor, the user topic to a collection of user topics;
determining, by the processor, whether one or more of the user topics are user suggested topics;
generating, by the processor, a topic for each of the user suggested topics; and
adding the collection of user topics to the plurality of known topics.

13. The method of claim 10 , further comprising:
receiving, by the processor, a plurality of blacklisted topics; and
removing, by the processor, all of the blacklisted topics from the one or more new topics.

14. A method for detecting one or more events in a portion of an interaction, given a plurality of known topics, the method comprising:
extracting, by a processor, a plurality of fragments from the portion of the interaction, each fragment of the plurality of fragments comprising one or more words;
initializing, by the processor, a collection of detected new fragments to an empty collection;
computing, by the processor, a similarity between each fragment and each of the known topics, each of the known topics comprising a template fragment comprising one or more template words, the similarity between a fragment of the fragments and a topic of the known topics being computed based on the one or more words of the fragment and the one or more template words of the template fragment of the topic;
identifying, by the processor, for each fragment, a corresponding topic having a highest similarity;
adding, by the processor, a fragment of the fragments to the collection of detected new fragments in response to the similarity between the fragment and the corresponding topic having the highest similarity being greater than a threshold value;
extracting, by the processor, one or more noun phrases from the collection of detected new fragments;
filtering, by the processor, one or more events from the one or more noun phra

Assignees

• Genesys Telecommunications Laboratories Inc

Inventors

• Lev Yoni
• Faizakof Avraham
• Lev-Tov Amir
• Tapuhi Tamir
• Konig Yochai

Classifications

• G06Q10/40

  Business processes related to social networking or social networking services · CPC title

• G06Q30/0281 Primary

  Customer communication at a business location, e.g. providing product or service information, consulting · CPC title

• G06Q50/01

  Physics · mapped topic

• G06F17/30976 Primary

  Physics · mapped topic

• G06F17/30713

  Physics · mapped topic