12. A method, performed on 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 method comprising the steps of: identifying whether the received new concept description has a normalized format, and if the received new concept description does not have a normalized format, transforming the new concept description of the un-normalized format into a normalized description, wherein said normalized concept description includes one or more description part(s) having kernel concepts, said description parts can only contain the terms which can be identified in said existing ontology, and each said kernel concept contains a headword and zero or more property(s); and 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, thereby generating an expression of the new concept based on existing ontologies; wherein the computing system comprises a processor coupled to a memory; and wherein if an 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 the related concepts that the i-th concept c i can reach in the directed graph G, then the step of identifying the headword in each normalized concept description part comprises the substeps of: for each concept ci in the description, computing s(c i ) the number of the concepts the concept ci can reach in the description part, and ∑ j = 1 n , j ≠ i ⁢ d ⁡ ( c i , c j ) , the sum of distances between the concept c i and all other concepts in the concept description; computing the importance D i of the concept c i by using s(c i ), the number of the concepts in the description part, and ∑ j = 1 n , j ≠ i ⁢ d ⁡ ( c i , c j ) , the sum of the distances between the concept c i and all other concepts in the concept description: D i ⁢ = def ⁢ s ⁡ ( c i ) ∑ j = 1 n , j ≠ i ⁢ d ⁡ ( c i , c j ) ; identifying the kernel concept c k in the description by using the importance D i of the concept c i wherein k is determined by the following formula: 
 (1 ≦k≦n )^( D k =Max( D i|j=1, n )).
12. A method, performed on 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 method comprising the steps of: identifying whether the received new concept description has a normalized format, and if the received new concept description does not have a normalized format, transforming the new concept description of the un-normalized format into a normalized description, wherein said normalized concept description includes one or more description part(s) having kernel concepts, said description parts can only contain the terms which can be identified in said existing ontology, and each said kernel concept contains a headword and zero or more property(s); and 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, thereby generating an expression of the new concept based on existing ontologies; wherein the computing system comprises a processor coupled to a memory; and wherein if an 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 the related concepts that the i-th concept c i can reach in the directed graph G, then the step of identifying the headword in each normalized concept description part comprises the substeps of: for each concept ci in the description, computing s(c i ) the number of the concepts the concept ci can reach in the description part, and ∑ j = 1 n , j ≠ i ⁢ d ⁡ ( c i , c j ) , the sum of distances between the concept c i and all other concepts in the concept description; computing the importance D i of the concept c i by using s(c i ), the number of the concepts in the description part, and ∑ j = 1 n , j ≠ i ⁢ d ⁡ ( c i , c j ) , the sum of the distances between the concept c i and all other concepts in the concept description: D i ⁢ = def ⁢ s ⁡ ( c i ) ∑ j = 1 n , j ≠ i ⁢ d ⁡ ( c i , c j ) ; identifying the kernel concept c k in the description by using the importance D i of the concept c i wherein k is determined by the following formula: 
 (1 ≦k≦n )^( D k =Max( D i|j=1, n )). 16. The method for creating new concepts in existing ontologies according to claim 12 , wherein the step of generating a new concept expression comprises the substeps of imposing property restrictions on the kernel concepts identified by the kernel concept identifier and/or performing intersection/union/complement operations on them.