ALERTING SYSTEM BASED ON NEWLY DISAMBIGUATED FEATURES

• US 20160162572A1
• Filed: 02/17/2016
• Published: 06/09/2016
• Est. Priority Date: 12/02/2013
• Status: Abandoned Application

• Current Assignee: Qbase, LLC
• Original Assignee: Qbase, LLC
• Inventors: Lightner, Scott, Weckesser, Franz
• Application Number:
  US15/045,828
• Publication Number:
  US 20160162572A1
• Time in Patent Office: Days
• CPC Class Codes: G06F 16/24 Querying
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/285 Clustering or classification
• CPC Class Codes: G06F 16/9024 Graphs; Linked lists G06F16/9027 takes precedence

Abstract

The present disclosure relates to a method of alerting users regarding newly disambiguated features. More specifically, a newly disambiguated feature may pass through different filters/restrictions, such as, the known knowledge base. The disclosed known knowledge base may filter the newly disambiguated feature, comparing the newly disambiguated features to the existing features to discover a new feature of interest. Particularly, the disclosed new feature of interest may include a new person, a new phone number, a new place, a new company, among others. Finally, if there is a new feature that did not match with the existing disambiguated features in the known knowledge base, then an alert may be emitted to a user.

Claims

1. A method comprising:

accessing, by a processor, a first document, wherein the processor is coupled to a memory, wherein the memory stores a first database containing a plurality of co-occurring document features;

extracting, by the processor, based on the accessing, a feature from the first document;

linking, by the processor, based on the extracting, the feature to a set of document features stored in a second database, wherein the set of document features comprises a primary feature and a secondary feature, wherein the set of document features is obtained from a second document, wherein the secondary feature includes a proximity cluster of co-occurring features in the second document;

disambiguating, by the processor, based on the linking, the feature from the first document;

adding, by the processor, based on the disambiguating, the feature to the first database based on the feature matching a document feature of interest in a third database based on the set of document features including the proximity cluster; and

in response to generating, by the processor, an alert informative of the matching, sending, by the processor, the alert.

2. The method of claim 1, further comprising:

assigning, by the processor, based on the disambiguating, a score to the feature, wherein the score is indicative of a level of confidence associated with a degree of disambiguation of the feature, wherein the feature matches the document feature of interest in the third database based on the score.

3. The method of claim 1, wherein the processor matches the feature with the document feature of interest in the third database based on a distance parameter associated with the proximity cluster.

4. The method of claim 1, wherein the processor matches the feature with the document feature of interest in the third database based on graph clustering of the secondary feature.

5. The method of claim 1, wherein the feature is selected from a group consisting of a person identifier, a phone number, a location, and a company name.

6. The method of claim 1, wherein the feature and the set of document features are linked temporarily.

7. A system comprising:

a server comprising a processor and a memory, wherein the processor is coupled to the memory, wherein the memory stores a first database containing a plurality of co-occurring document features, wherein the processor is instructed to;

access a first document;

extract, based on the accessing, a feature from the first document;

link, based on the extracting, the feature to a set of document features stored in a second database, wherein the set of document features comprises a primary feature and a secondary feature, wherein the set of document features is obtained from a second document, wherein the secondary feature includes a proximity cluster of co-occurring features in the second document;

disambiguate, based on the linking, the feature from the first document;

add, based on the disambiguating, the feature to the first database based on the feature matching a document feature of interest in a third database based on the set of document features including the proximity cluster; and

send an alert to a client in response to the processor generating the alert, wherein the alert is informative of the matching.

8. The system of claim 7, wherein the processor is instructed to:

assign, based on the disambiguating, a score to the feature, wherein the score is indicative of a level of confidence associated with a degree of disambiguation of the feature, wherein the feature matches the document feature of interest in the third database based on the score.

9. The system of claim 7, wherein the processor matches the feature with the document feature of interest in the third database based on a distance parameter associated with the proximity cluster.

10. The system of claim 7, wherein the processor matches the feature with the document feature of interest in the third database based on graph clustering of the secondary feature.

11. The system of claim 7, wherein the feature is selected from a group consisting of a person identifier, a phone number, a location, and a company name.

12. The system of claim 7, wherein the feature and the set of document features are linked temporarily.