1. A computing system for creating new concepts in existing ontologies based on new concept descriptions expressed in a natural language format, wherein words in a natural language are transformed into a certain language for expressing the new concepts in the existing ontologies, the computing system comprising a processor coupled to a memory and operative to implement: a normalizer for receiving and parsing the new concept descriptions so as to transform them into normalized ones and output them, wherein said normalized concept description includes one or more description part(s) having kernel concepts, said descriptions parts can only contain the terms which can be identified in said existing ontology, and each of said kernel concept contains a headword and a zero or more property(s); and a new concept factory for, based on the normalized description of the new concept, identifying the kernel concepts in each normalized concept description part, and extracting the identified kernel concepts, related properties, and the relations among the kernel concepts for a user to create new concepts according to existing ontologies; wherein the new concept factory comprises a kernel concept identifier for receiving the normalized new concept description, identifying the kernel concepts in each normalized concept description part, and extracting the identified kernel concepts, the related properties, and the relations among the kernel concepts; wherein an existing ontology is viewed as a directed graph G, where concepts are nodes and a relationship between two concepts is a directed edge; given n concepts, let c i denote the i-th concept, and let d(c i , c j ) be the distance between the i-th concept c i and the j-th concept c j in the directed graph G, s(node i ) be the total number of related concepts that the i-th concept c i can reach in the directed graph G, s(c i ) be the number of concepts the concept c i can reach in the description part and ∑ j = 1 n , j ≠ i ⁢ d ⁡ ( c i , c j ) be the sum of distances between the concept c i and all other concepts in the concept description, the importance D i of the concept c i can be calculated by the kernel concept identifier according to the following formula; D i ⁢ = def ⁢ s ⁡ ( c i ) ∑ j = 1 n , j ≠ i ⁢ d ⁡ ( c i , c j ) and the kernel concept c k in the description is thus obtained, wherein k can be determined by the following formula: 
 (1≦ k≦n )^( D k =Max( D i|j=1,n )).