Method for entity-driven alerts based on disambiguated features

Abstract

A method for entity-driven alerts based on disambiguated features, is disclosed. According to an embodiment, disclosed method may refer to entity-driven alerts based on trending or new knowledge of a disambiguated feature. The alerts may be sent to a user when new knowledge is discovered about the disambiguated feature, a new association (such as new features, facts, quotations, or topic IDs related, among others) with the feature of interest, and/or new trending changes are emerging about the feature of interest. According to various embodiments, method for entity-driven alerts based on disambiguated features may reduce the number of false positives resulting in a normal search query. Which in turn, may increase the efficiency of monitoring, allowing for broadened universe of alerts.

What is claimed is: 
     
         1 . A method comprising:
 accessing, by a server, an electronic document stored in an in-memory database;   extracting, by the server, a first feature from content data of the electronic document having one or more features;   disambiguating, by the server, the first feature from the content data;   comparing, by the server, the first feature to a second feature stored in the in-memory database;   in response to the first feature matching the second feature, comparing, by the server, the first feature to a third feature stored in the in-memory database;   in response to the first feature not matching the third feature, determining, by the server, if the first feature is representative of a knowledge new to the in-memory database;   in response of the first feature being representative of the knowledge, updating, by the server, the in-memory database with the first feature;   generating, by the server, a message informative of the first feature based on the updating; and   sending, by the server, the message to a client.   
     
     
         2 . The method of  claim 1 , wherein the first feature is stored in a first data structure of the in-memory database, and the second feature is stored in a second data structure of the in-memory database. 
     
     
         3 . The method of  claim 2 , wherein the first data structure is distinct from the second data structure. 
     
     
         4 . The method of  claim 1 , further comprising:
 assigning, by the server, a score to the first feature, wherein the score is indicative of a level of confidence associated with a degree of disambiguation based on the disambiguating, wherein the first feature matches the second feature based on the score;   storing, by the server, the score in the in-memory database such that the score is associated with the first feature;   granting, by the server, a read access for the score to the client.   
     
     
         5 . The method of  claim 1 , wherein the updating is based on a distance in text from a link location in the electronic document, wherein the distance is based on a closeness in text to the link location. 
     
     
         6 . The method of  claim 1 , wherein the knowledge is indicative of an association new to the in-memory database, wherein the association is between the first feature with a fourth feature stored in the in-memory database. 
     
     
         7 . The method of  claim 1 , wherein the message is a first message, and further comprising:
 associating, by the server, the first feature with a plurality of documents stored in the in-memory database;   determining, by the server, a quantity of the documents;   accessing, by the server, a threshold stored in the in-memory database, wherein the threshold is set via the client;   determining, by the server, if the quantity meets or exceeds the threshold;   in response to the quantity meeting or exceeding the threshold, generating, by the server, a second message informative of at least one of the meeting or the exceeding; and   sending, by the server, the second message to the client.   
     
     
         8 . The method of  claim 7 , wherein the threshold comprises a daily average number of the documents associated with the first feature in the in-memory database. 
     
     
         9 . The method of  claim 1 , wherein the disambiguating comprises linking, by the server, the first feature to a fourth feature stored in the in-memory database, wherein the in-memory database stores a plurality of co-occurring features obtained from a plurality of electronic documents comprising the electronic document. 
     
     
         10 . The method of  claim 9 , wherein the linking is dynamic based on a predetermined factor. 
     
     
         11 . A method comprising:
 accessing, by a server, an electronic document stored in an in-memory database;   extracting, by the server, a first feature from the electronic document;   disambiguating, by a server, the first feature;   comparing, by the server, the first feature to a second feature stored in the in-memory database;   in response to the first feature matching the second feature, comparing, by the server, the first feature to a third feature stored in the in-memory database;   in response to the first feature not matching the third feature, determining, by the server, if the first feature is representative of an association new to the in-memory database, wherein the association is between the first feature with a fourth feature stored in the in-memory database;   in response of the first feature being representative of the association, updating, by the server, the in-memory database with the first feature;   generating, by the server, a message informative of the first feature based on the updating; and   sending, by the server, the message to a client.   
     
     
         12 . The method of  claim 11 , wherein the first feature is stored in a first data structure in the in-memory database and the second feature is stored in a second data structure in the in-memory database. 
     
     
         13 . The method of  claim 12 , wherein the first data structure is distinct from the second data structure. 
     
     
         14 . The method of  claim 11 , further comprising:
 assigning, by the server, a score to the first feature, wherein the score is indicative of a level of confidence associated with a degree of disambiguation based on the disambiguating, wherein the first feature matches the second feature based on the score;   storing, by the server, the score in the in-memory database such that the score is associated with the first feature;   granting, by the server, a read access for the score to the client.   
     
     
         15 . The method of  claim 11 , wherein the updating is based on a distance in text from a link location in the electronic document, wherein the distance is based on a closeness in text to the link location. 
     
     
         16 . The method of  claim 11 , wherein the message is a first message, and further comprising:
 associating, by the server, the first feature with a plurality of documents stored in the in-memory database;   determining, by the server, a quantity of the documents;   accessing, by the server, a threshold stored in the in-memory database, wherein the threshold is set via the client;   determining, by the server, if the quantity meets or exceeds the threshold;   in response to the quantity meeting or exceeding the threshold, generating, by the server, a second message informative of at least one of the meeting or the exceeding; and   sending, by the server, the second message to the client.   
     
     
         17 . The method of  claim 16 , wherein the threshold comprises a daily average number of the documents associated with the first feature in the in-memory database. 
     
     
         18 . The method of  claim 11 , wherein the disambiguating comprises linking, by the server, the first feature to a fourth feature stored in the in-memory database, wherein the in-memory database stores a plurality of co-occurring features obtained from a plurality of electronic documents comprising the electronic document. 
     
     
         19 . The method of  claim 18 , wherein the linking is dynamic based on a predetermined factor.