Method for disambiguated features in unstructured text

Abstract

A method for disambiguating features in unstructured text is provided. The disclosed method may not require pre-existing links to be present. The method for disambiguating features in unstructured text may use co-occurring features derived from both the source document and a large document corpus. The disclosed method may include multiple modules, including a linking module for linking the derived features from the source document to the co-occurring features of an existing knowledge base. The disclosed method for disambiguating features may allow identifying unique entities from a knowledge base that includes entities with a unique set of co-occurring features, which in turn may allow for increased precision in knowledge discovery and search results, employing advanced analytical methods over a massive corpus, employing a combination of entities, co-occurring entities, topic IDs, and other derived features.

What is claimed is: 
     
         1 . A method comprising:
 in response to receiving, by a server, a search query from a client:
 searching, by the server, a set of records comprising a co-occurring feature, wherein the server comprises a main memory hosting a database, wherein the database stores a first cluster, wherein the first cluster comprises a disambiguated primary feature with a unique identifier and a set of secondary features, wherein the first cluster comprises a first score; 
 identifying, by the server, a record in the set of records, wherein the record matches an extracted feature such that the extracted feature is a primary feature; 
 associating, by the server, the extracted feature with a topic identifier; 
 disambiguating, by the server, the primary feature based on a relatedness of the topic identifier; 
 identifying, by the server, the set of secondary features based on the relatedness; 
 disambiguating, by the server, the primary feature from the set of secondary features based on the relatedness; 
 accessing, by the server, the database; 
   linking, by the server, in real-time, during the accessing, the primary feature to the set of secondary features;
 forming, by the server, a second cluster based on the linking, wherein the second cluster comprises a second score; 
   comparing, by the server, the first score against the second score;   determining, by the server, whether the first score matches the second score;   identifying, by the server, the unique identifier related to the primary feature in the first cluster based on the first score matching the second score;   amending, by the server, based on the identifying the unique identifier, the first cluster such that the first cluster includes the second cluster; and   sending, by the server, the unique identifier to the client.   
     
     
         2 . The method of  claim 1 , further comprising:
 comparing, by the server, each member of the set of records which matches the extracted feature against a data item;   assigning, by the server, a third score to the extracted feature based on the comparing of the each of the member.   
     
     
         3 . The method of  claim 2 , further comprising:
 associating, by the server, the extracted feature with a feature attribute.   
     
     
         4 . The method of  claim 3 , wherein the feature attribute is weighted. 
     
     
         5 . The method of  claim 2 , further comprising:
 determining, by the server, a relatedness of the extracted feature based on the feature attribute.   
     
     
         6 . The method of  claim 1 , wherein the primary feature is associated with a feature attribute. 
     
     
         7 . The method of  claim 1 , wherein the extracted feature is associated with a lower-ordinal feature in accordance with a cluster hierarchy. 
     
     
         8 . The method of  claim 1 , wherein the searching is in a fuzzy manner. 
     
     
         9 . The method of  claim 1 , further comprising:
 comparing, by the server, a first feature against a second feature, wherein the first feature comprises the extracted feature, wherein the first feature is provided via a first data source, wherein the second feature is provided via a second data source;   
       determining, by the server, if the first feature co-occurs in the second data source based on the comparing of the first feature against the second feature; 
       linking, by the server, at least one of the first data source or the second data source. 
     
     
         10 . The method of  claim 1 , further comprising:
 determining, by the server, a co-occurrence of the extracted feature in a plurality of data sources;   improving, by the server, a rate of accuracy of the disambiguating based on the determining of the co-occurrence of the extracted feature.   
     
     
         11 . A method comprising:
 in response to receiving, by a server, a search query from a client:
 searching, by the server, based on the receiving, a set of records comprising a co-occurring feature, wherein the server comprises a main memory hosting a database, wherein the database stores a first cluster, wherein the first cluster comprises a disambiguated primary feature with a first unique identifier and a set of secondary features, wherein the first cluster comprises a first score; 
 identifying, by the server, a record in the set of records, wherein the record matches an extracted feature such that the extracted feature is a first primary feature; 
 associating, by the server, the extracted feature with a topic identifier; 
 disambiguating, by the server, the first primary feature based on a relatedness of the topic identifier; 
 identifying, by the server, the set of secondary features based on the relatedness; 
 disambiguating, by the server, the first primary feature from the set of secondary features based on the relatedness; 
 accessing, by the server, the database; 
   linking, by the server, in real-time, during the accessing, the first primary feature to the set of secondary features;
 forming, by the server, a second cluster based on the linking, wherein the second cluster comprises a second score; 
   comparing, by the server, the first score against the second score;   determining, by the server, whether the first score matches the second score;   generating, by the server, a third cluster based on the first score not matching the second score, wherein the third cluster comprises a second primary feature;   assigning, by the server, a second unique identifier to the second primary feature;   sending, by the server, the second unique identifier to the client.   
     
     
         12 . The method of  claim 1 , further comprising:
 comparing, by the server, each member of the set of records which matches the extracted feature against a data item;   assigning, by the server, a third score to the extracted feature based on the comparing of the each of the member.   
     
     
         13 . The method of  claim 2 , further comprising:
 associating, by the server, the extracted feature with a feature attribute.   
     
     
         14 . The method of  claim 3 , wherein the feature attribute is weighted. 
     
     
         15 . The method of  claim 2 , further comprising:
 determining, by the server, a relatedness of the extracted feature based on the feature attribute.   
     
     
         16 . The method of  claim 1 , wherein at least one of the first primary feature or the second primary feature is associated with a feature attribute. 
     
     
         17 . The method of  claim 1 , wherein the extracted feature is associated with a lower-ordinal feature in accordance with a cluster hierarchy. 
     
     
         18 . The method of  claim 1 , wherein the searching is in a fuzzy manner. 
     
     
         19 . The method of  claim 1 , further comprising:
 comparing, by the server, a first feature against a second feature, wherein the first feature comprises the extracted feature, wherein the first feature is provided via a first data source, wherein the second feature is provided via a second data source;   
       determining, by the server, if the first feature co-occurs in the second data source based on the comparing of the first feature against the second feature; 
       linking, by the server, at least one of the first data source or the second data source. 
     
     
         20 . The method of  claim 1 , further comprising:
 determining, by the server, a co-occurrence of the extracted feature in a plurality of data sources;   improving, by the server, a rate of accuracy of the disambiguating based on the determining of the co-occurrence of the extracted feature.