1. A computer system configured to find correspondence between terms in two different languages, the system comprising: a unit configured to create a technical term set in a first language, a general term set in the first language, a technical term set in a second language and a general term set in the second language; a storage unit for storing the term set of the first language, the general term set in the first language, the technical terms set in the second language and the general term in the second language; a unit configured to create at least two bipartite graphs, wherein the first bipartite graph connects the technical term set and the general term set of the first language to each other with links on the basis of corpus information, wherein the second bipartite graph connects the general term set and technical term set of the second language to each other with links on the basis of corpus information, and wherein each of the links is weighted by a degree of association between terms; a unit configured to create a third bipartite graph by creating links between general terms in the first language and general terms in the second language by using a translation dictionary between general terms in the first language and general terms in the second language, each of the links being weighted by a degree of association between terms; a unit configured to create an association matrix M including the bipartite graphs between the technical term set and the general term set connected in each respective language and the bipartite graph between the general terms in the first language and the general terms in the second language, wherein the association matrix M is normalized such that a sum of each row is equal to one; a unit configured to calculate a similarity matrix Q by calculation of an inverse matrix (I−cM) of a matrix in which only a portion corresponding to both of the general term set in the first language and the technical term set in the first language and a portion corresponding to both of the general term set in the second language and the technical term set in the second language are left, where c is a positive number smaller than one; and a unit configured to output correspondence between the technical term set in the first language and the technical term set in the second language on the basis of predetermined components of the similarity matrix Q, wherein said unit configured to create the association matrix M includes creating a set of submatrices comprising: a submatrix created on the basis of links between the technical term set and the general term set in a first language and its transposed submatrix, a submatrix created on the basis of links between the technical term set and the general term set in a second language and its transposed submatrix, and a submatrix created on the basis of links between the general term set in the first language and the general term set in the second language and its transposed submatrix.
1. A computer system configured to find correspondence between terms in two different languages, the system comprising: a unit configured to create a technical term set in a first language, a general term set in the first language, a technical term set in a second language and a general term set in the second language; a storage unit for storing the term set of the first language, the general term set in the first language, the technical terms set in the second language and the general term in the second language; a unit configured to create at least two bipartite graphs, wherein the first bipartite graph connects the technical term set and the general term set of the first language to each other with links on the basis of corpus information, wherein the second bipartite graph connects the general term set and technical term set of the second language to each other with links on the basis of corpus information, and wherein each of the links is weighted by a degree of association between terms; a unit configured to create a third bipartite graph by creating links between general terms in the first language and general terms in the second language by using a translation dictionary between general terms in the first language and general terms in the second language, each of the links being weighted by a degree of association between terms; a unit configured to create an association matrix M including the bipartite graphs between the technical term set and the general term set connected in each respective language and the bipartite graph between the general terms in the first language and the general terms in the second language, wherein the association matrix M is normalized such that a sum of each row is equal to one; a unit configured to calculate a similarity matrix Q by calculation of an inverse matrix (I−cM) of a matrix in which only a portion corresponding to both of the general term set in the first language and the technical term set in the first language and a portion corresponding to both of the general term set in the second language and the technical term set in the second language are left, where c is a positive number smaller than one; and a unit configured to output correspondence between the technical term set in the first language and the technical term set in the second language on the basis of predetermined components of the similarity matrix Q, wherein said unit configured to create the association matrix M includes creating a set of submatrices comprising: a submatrix created on the basis of links between the technical term set and the general term set in a first language and its transposed submatrix, a submatrix created on the basis of links between the technical term set and the general term set in a second language and its transposed submatrix, and a submatrix created on the basis of links between the general term set in the first language and the general term set in the second language and its transposed submatrix. 2. The system according to claim 1 , wherein the degree of association between the technical term set and the general term set corresponding to a same language in each of the bipartite graphs is either a co-occurrence frequency or a degree of co-occurrence correlation between terms.