1. A computer-implemented method for performing fuzzy full text search, comprising: receiving a first search term and a second search term; identifying an error threshold distance for a combination of the first term and the second term; exploring paths of an inverted token next valid character tree, wherein each path in the inverted token next valid character tree corresponds to a document in a document list; computing a first document error list for each path that reaches a leaf node in the tree, wherein the first document error list includes a document identifier located at the leaf node reached in the inverted token next valid character tree and a first error distance for the number of edit operations to transform the token associated with the document identifier to the first search term; computing a second document error list for each path that reaches a leaf node in the tree, wherein the second document error list includes a document identifier located at the leaf node reached in the inverted token next valid character tree and a second error distance for the number of edit operations to transform the token associated with the document identifier to the first search term; comparing the first document error list to the second document error list to identify common document identifiers with a sum of the first error distance and the second error distance is less than or equal to the threshold error distance for the combination of the first search term and the second search term; adding the common document identifiers to a result set; and providing the result set of document identifiers.
1. A computer-implemented method for performing fuzzy full text search, comprising: receiving a first search term and a second search term; identifying an error threshold distance for a combination of the first term and the second term; exploring paths of an inverted token next valid character tree, wherein each path in the inverted token next valid character tree corresponds to a document in a document list; computing a first document error list for each path that reaches a leaf node in the tree, wherein the first document error list includes a document identifier located at the leaf node reached in the inverted token next valid character tree and a first error distance for the number of edit operations to transform the token associated with the document identifier to the first search term; computing a second document error list for each path that reaches a leaf node in the tree, wherein the second document error list includes a document identifier located at the leaf node reached in the inverted token next valid character tree and a second error distance for the number of edit operations to transform the token associated with the document identifier to the first search term; comparing the first document error list to the second document error list to identify common document identifiers with a sum of the first error distance and the second error distance is less than or equal to the threshold error distance for the combination of the first search term and the second search term; adding the common document identifiers to a result set; and providing the result set of document identifiers. 4. The method of claim 1 , further comprising retrieving documents associated with the document identifiers in the result set.