Alerting system based on newly disambiguated features

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.

What is claimed is: 
     
         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.