Domain centric natural language query answering

Abstract

Embodiments of the present invention disclose a method, computer program product, and system for searching a database using a user entered search query. A search query for a database is received by the computer and the computer applies condition-action rules based on natural language processing rules to identify one or more phrases within the search query that is associated an entity identifier. The computer further identifies any taxonomy variants that have been established for the identified phrases. The computer creates a search string that includes search query and the entity identifiers. The database search is conducted by the computer and the results are displayed for the user.

What is claimed is: 
     
         1 . A method for searching a database using a user entered search query, the method comprising:
 receiving, by a computer, a user entered search query;   identifying, by a computer, one or more phrases in the search query   comparing, by the computer, the one or more phrases to an entity identifier database to determine whether the one or more phrases are associated with one or more entity identifiers in the entity identifier database by applying condition-action rules based on performing natural language processing (NLP) rules to the search query;   identifying, by the computer, taxonomy variants for the one or more phrases; and   creating, by a computer, a search string that includes the search query, the associated entity identifiers, and the identified taxonomy variants.   
     
     
         2 . The method of  claim 1 , further comprising:
 searching, by the computer, a database using the created search string;   ranking the database search results in order to determine which database search result to display when multiple different search results have been returned when conducting the database search, wherein the ranking of the database search results is based on two or more of: a department the user works for, a position of the user, user statistics; and   displaying, by the computer, the database search results.   
     
     
         3 . The method of  claim 1 , wherein the entity database is an internal schema that is applied to data contained within the database. 
     
     
         4 . The method of  claim 1 , wherein the one or more entity identifiers comprise at least one of the group comprising: a product, a time interval, a brand, a type of service, and a location. 
     
     
         5 . The method of  claim 1 , wherein the applying condition-action rules based on performing natural language processing (NLP) rules to the search query further comprises:
 applying, by the computer, the condition-action rules to a phrase in the search query containing a single word;   increasing, by the computer, the phrase containing a single word to a phrase containing at least one additional word; and   reapplying, by the computer, the condition-action rules to the increased phrase.   
     
     
         6 . The method of  claim 2 , wherein the ranking of the database search results comprises determining, by the computer, if there is a statistical trend in a subject matter for the query and ranking the multiple different search results to reflect the statistical trend of the subject matter. 
     
     
         7 . The method of  claim 2 , wherein the ranking of the database search results comprises determining, by the computer, an ambiguity score for the database search results, the ambiguity score being based on at least one of the group comprising: the number of search results being returned, an error in the search query and an error in the search string. 
     
     
         8 . A computer program product for searching a database using a user entered search query, the computer program product comprising:
 one or more non-transitory computer-readable storage media and program instructions stored on the one or more non-transitory computer-readable storage media, the program instructions comprising:
 receiving a user entered search query; 
 identifying one or more phrases in the search query, 
 comparing, by the computer, the one or more phrases to an entity identifier database to determine whether the one or more phrases are associated with one or more entity identifiers in the entity identifier database by applying condition-action rules based on performing natural language processing (NLP) rules to the search query; 
 identifying, by the computer, taxonomy variants for the one or more phrases; and 
 creating a search string that includes the search query, the associated entity identifiers, and the identified taxonomy variants. 
   
     
     
         9 . The computer program product of  claim 1 , further comprising:
 searching a database using the created search string;   ranking the database search results in order to determine which database search result to display when multiple different search results have been returned when conducting the database search, wherein the ranking of the database search results is based on two or more of: a department the user works for, a position of the user, user statistics; and   displaying the database search results.   
     
     
         10 . The computer program product of  claim 8 , wherein the entity database is an internal schema that is applied to data contained within the database. 
     
     
         11 . The computer program product of  claim 8 , wherein the one or more entity identifiers comprise at least one of the group comprising: a product, a time interval, a brand, a type of service, and a location. 
     
     
         12 . The computer program product of  claim 8 , wherein the applying condition-action rules based on performing natural language processing (NLP) rules to the search query further comprises:
 applying, by the computer, the condition-action rules to a phrase in the search query containing a single word;   increasing, by the computer, the phrase containing a single word to a phrase containing at least one additional word; and   reapplying, by the computer, the condition-action rules to the increased phrase.   
     
     
         13 . The computer program product of  claim 9 , wherein the ranking of the database search results comprises determining, by the computer, if there is a statistical trend in a subject matter for the query and ranking the multiple different search results to reflect the statistical trend of the subject matter. 
     
     
         14 . The computer program product of  claim 9 , wherein the ranking of the database search results comprises determining, by the computer, an ambiguity score for the database search results, the ambiguity score being based on at least one of the group comprising: the number of search results being returned, an error in the search query and an error in the search string 
     
     
         15 . A computer system for searching a database using a user entered search query the computer system comprising:
 one or more computer processors, one or more computer-readable storage media, and program instructions stored on one or more of the computer-readable storage media for execution by at least one of the one or more processors, the program instructions comprising:
 receiving a user entered search query; 
 identifying one or more phrases in the search query,. 
 comparing, by the computer, the one or more phrases to an entity identifier database to determine whether the one or more phrases are associated with one or more entity identifiers in the entity identifier database by applying condition-action rules based on performing natural language processing (NLP) rules to the search query; 
 identifying, by the computer, taxonomy variants for the one or more phrases; and 
 creating a search string that includes the search query, the associated entity identifiers, and the identified taxonomy variants. 
   
     
     
         16 . The computer system of  claim 15 , further comprising:
 searching a database using the created search string;   ranking the database search results in order to determine which database search result to display when multiple different search results have been returned when conducting the database search, wherein the ranking of the database search results is based on two or more of: a department the user works for, a position of the user, user statistics; and   displaying the database search results.   
     
     
         17 . The computer system of  claim 15 , wherein the entity database is an internal schema that is applied to data contained within the database. 
     
     
         18 . The computer system of  claim 15 , wherein the one or more entity identifiers comprise at least one of the group comprising: a product, a time interval, a brand, a type of service, and a location. 
     
     
         19 . The computer system of  claim 15 , wherein the applying condition-action rules based on performing natural language processing (NLP) rules to the search query further comprises:
 applying, by the computer, the condition-action rules to a phrase in the search query containing a single word;   increasing, by the computer, the phrase containing a single word to a phrase containing at least one additional word; and   reapplying, by the computer, the condition-action rules to the increased phrase.   
     
     
         20 . The computer system of  claim 16 , wherein the ranking of the database search results further comprises:
 determining, by the computer, if there is a statistical trend in a subject matter for the query and ranking the multiple different search results to reflect the statistical trend of the subject matter; and   determining, by the computer, an ambiguity score for the multiple different search results, the ambiguity score being based on at least one of the group comprising: the number of search results being returned, an error in the search query and an error in the search string.