13. The computer program product according to claim 11 , wherein the correlation value is acquired from a first data set of pieces of document data containing each keyword in a classification keyword set, a second data set of pieces of document data with the respective third scores that are equal to or more than the predetermined threshold or are included in the predetermined high-ranking proportion, a third data set of pieces of document data containing the search keyword or the relevant keyword, and a common data set of pieces of document data existing in both the first data set and the second data set.
13. The computer program product according to claim 11 , wherein the correlation value is acquired from a first data set of pieces of document data containing each keyword in a classification keyword set, a second data set of pieces of document data with the respective third scores that are equal to or more than the predetermined threshold or are included in the predetermined high-ranking proportion, a third data set of pieces of document data containing the search keyword or the relevant keyword, and a common data set of pieces of document data existing in both the first data set and the second data set. 14. The computer program product according to claim 13 , wherein the correlation value is acquired according to a correlation function corr total (s,t) described below: Equation ⁢ ⁢ 5 corr total ⁡ ( s , t ) = 1 1 + a · [ corr regular ⁡ ( s , t ) + a ] · corr concept ⁡ ( s , t ) n [ E ⁢ ⁢ 5 ] where a and n are adjustable parameters, Equation ⁢ ⁢ 6 corr regular ⁡ ( s , t ) = P regular ⁡ ( s ⋂ t ) P regular ⁡ ( s ) ⁢ P regular ⁡ ( t ) [ E ⁢ ⁢ 6 ] Equation ⁢ ⁢ 7 P regular ⁡ ( s ) = 1 N ⁢ ∑ d = documents ⁢ ⁢ δ s , d [ E ⁢ ⁢ 7 ] Equation ⁢ ⁢ 8 P regular ⁡ ( t ) = 1 N ⁢ ∑ d = documents ⁢ ⁢ δ t , d [ E ⁢ ⁢ 8 ] Equation ⁢ ⁢ 9 P regular ⁡ ( s ⋂ t ) = 1 N ⁢ ∑ d = documents ⁢ ⁢ δ s , d ⁢ δ t , d [ E ⁢ ⁢ 9 ] where s is a facet keyword, t is a search keyword, d is document data, N is a total number of pieces of document data, δ s,d is one in a case where the facet keyword s is included in the document data d and zero in the other cases, δ t,d is one in a case where the search keyword t is included in the document data d and zero in the other cases, Equation ⁢ ⁢ 10 corr concept ⁡ ( s , t ) = P concept ⁡ ( s ⋂ t ) P concept ⁡ ( s ) ⁢ P concept ⁡ ( t ) [ E ⁢ ⁢ 10 ] Equation ⁢ ⁢ 11 P concept ⁡ ( s ) = 1 N ⁢ ∑ d = documents ⁢ ⁢ 〈 s ❘ d 〉 [ E ⁢ ⁢ 11 ] Equation ⁢ ⁢ 12 P concept ⁡ ( t ) = 1 N ⁢ ∑ d = documents ⁢ ⁢ 〈 t ❘ d 〉 [ E ⁢ ⁢ 12 ] Equation ⁢ ⁢ 13 P concept ⁡ ( s ⋂ t ) = 1 N ⁢ ∑ d = documents ⁢ ⁢ 〈 s ❘ d 〉 ⁢ 〈 t ❘ d 〉 [ E ⁢ ⁢ 13 ] where s is a facet keyword, t is a search keyword, d is document data, N is a total number of pieces of document data, <s|d> is Σs i ×d i (Σ is a sum regarding i=1, 2, . . . , k), <t|d> is Σt i ×d i (Σ is a sum regarding i=1, 2, . . . , k), and k is a total number of clusters and an integer.