Method, system, and computer program product for dividing a term with appropriate granularity

Abstract

A method, computer system, and computer program product for dividing a term with appropriate granularity includes extracting an element word specifying granularity from content by parsing, and, if the term includes at least one element word in a part thereof, dividing the term at a position where the at least one element word exists.

1 . A method for dividing a term with appropriate granularity, the method comprising:
 extracting an element word specifying granularity from content by parsing; and   when the term includes at least one element word, dividing the term, by a processor, at a position where the at least one element word exists.   
     
     
         2 . The method according to  claim 1 , wherein dividing the term at the position where the at least one element word exists comprises:
 if the term includes an element word that is a longest-match element word from an end of the term, dividing the term at a position where the longest-match element word from the end exists.   
     
     
         3 . The method according to  claim 2 , wherein dividing the term at a position where the at least one element word exists comprises:
 removing the longest-match element word from the end from the term to provide a remainder term; and   if the remainder term includes an element word that is a longest-match element word from a top of the remainder term, dividing the remainder term at a position where the longest-match element word from the top exists.   
     
     
         4 . The method according to  claim 2 , further comprises storing the longest-match element word from the end as a main term of the term. 
     
     
         5 . The method according to  claim 3 , further comprises storing the longest-match element word from the top as a first modifier of the term. 
     
     
         6 . The method according to  claim 5 , further comprises storing a part other than the longest-match element word from the top as a second modifier of the term. 
     
     
         7 . The method according to  claim 1 , wherein extracting the element word comprises:
 extracting phrases by applying the parsing to each piece of text in the content to provide extracted phrases; and   extracting a part from the extracted phrases that include a noun or a mark to provide an element word candidate.   
     
     
         8 . The method according to  claim 7 , wherein:
 extracting the element word further comprises cutting out pieces of text, from the content, from which the element word is to be extracted to provide cut-out pieces of text; and   extracting the phrases further comprises applying the parsing to each of the cut-out pieces of text.   
     
     
         9 . The method according to  claim 8 , wherein:
 extracting the element word further comprises dividing the cut-out pieces of text at a place where a predefined character exists to provide divided pieces of text; and   extracting the phrases further comprises applying the parsing to each of the divided pieces of text.   
     
     
         10 . The method according to  claim 7 , wherein:
 the term is a term in a term list; and   extracting the element word further comprises deleting the term existing in the term list from the element word candidate and setting the remainder as the element word.   
     
     
         11 . The method according to  claim 1 , wherein dividing the term at a position where the at least one element word exists comprises:
 dividing the term at the position where the element word exists in accordance with a division parameter specifying a number of divisions set in advance.   
     
     
         12 . The method according to  claim 1 , wherein the term is a term in a term list. 
     
     
         13 . The method according to  claim 1 , wherein the term is a term longer than a predetermined length in the content. 
     
     
         14 . The method according to  claim 1 , wherein the term is a word string that includes a noun, a mark or a combination thereof. 
     
     
         15 . The method according to  claim 1 , wherein the term is a compound noun. 
     
     
         16 . The method according to  claim 1 , wherein the element word is a string of one or multiple words that includes at least one noun or mark. 
     
     
         17 . A computer system for dividing a term with appropriate granularity, the computer system comprising:
 an extraction means configured to extract an element word specifying granularity from content by parsing; and   a division means configured to, when the term includes at least one element word, divide the term at a position where the at least one element word exists.   
     
     
         18 . The computer according to  claim 17 , wherein:
 if the term includes an element word that is a longest-match element word from an end of the term, the division means is further configured to divide the term at a position where the longest-match element word from the end exists.   
     
     
         19 . The computer according to  claim 18 , wherein the division means is further configured to:
 remove the longest-match element word from the end from the term to provide a remainder term; and   if the remainder term includes an element word that is a longest-match element word from a top of the remainder term, divide the remainder term at a position where the longest-match element word from the top exists.   
     
     
         20 . A computer program product for dividing a term with appropriate granularity, the computer program product which, when executed, causes a computer to execute the method according to  claim 1 .