A response generation apparatus ensures accurate output. A computer stores graph knowledge including a response generation module generating a response to an input document including a plurality of sentences, the graph knowledge database includes graph data that manages a structure of each type of graph knowledge, and the response generation module generates a first graph knowledge from each of the sentences; searches a second graph knowledge similar to each of the plurality of first graph knowledge while referring to the graph data on the basis of the plurality of first graph knowledge; identifies the plurality of second graph knowledge included in a dense location where a density of the second graph knowledge is high in a graph space; searches third graph knowledge for generating the response while referring to the graph data on the basis of the identified second graph knowledge; and generates the response using the third graph knowledge.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A computer comprising a processor, a storage device connected to the processor, and an interface connected to the processor, wherein the computer holds a graph type knowledge database that stores graph type knowledges each representing a relevance among elements constituting a sentence that defines a knowledge using a node and an edge, the computer includes a response generation module that generates a response to an input document including a plurality of sentences using the graph type knowledge database, the graph type knowledge database includes graph data that manages a structure of each of the graph type knowledges, and the response generation module is configured to: generate a first graph type knowledge from each of the sentences included in the input document; search a second graph type knowledge similar to each of the plurality of first graph type knowledges while referring to the graph data on the basis of the plurality of first graph type knowledges; identify the plurality of second graph type knowledges included in a dense location where a density of the plurality of second graph type knowledges is high in a graph space corresponding to the graph type knowledge database as the second graph type knowledges used to generate the response; search third graph type knowledges for generating the response while referring to the graph data on the basis of the identified second graph type knowledges; and generate the response using the third graph type knowledges. 2. The computer according to claim 1, wherein the response generation module is configured to: select a second graph type knowledge of interest; and identify the dense location where the density of the plurality of second graph type knowledges is high in the graph space on the basis of a distance between the node included in the second graph type knowledge of interest and the node included in each of others of the second graph type knowledges. 3. The computer according to claim 2, wherein the response generation module determines that the second graph type knowledge of interest is placed in the dense location if the distance is smaller than a threshold. 4. The computer according to claim 3, wherein the graph type knowledge database includes attribute data that manages an attribute indicating a condition for making each of the graph type knowledges hold, and the response generation module is configured to: calculate a score indicating consistency, in the condition for making each of the graph type knowledges hold, between each of the identified second graph type knowledges and each of the third graph type knowledges while referring to the attribute data; select the third graph type knowledge used for generating the response on the basis of the score; and generate the response on the basis of the selected third graph type knowledge. 5. The computer according to claim 4, the computer holding response type information that defines a type of the response to be output, wherein the response generation module searches the third graph type knowledges on the basis of the identified second graph type knowledges and the response type information. 6. A response generation method in a computer comprising a processor, a storage device connected to the processor, and an interface connected to the processor, the computer holding a graph type knowledge database that stores graph type knowledges each representing a relevance among elements constituting a sentence that defines a knowledge using a node and an edge, the computer including a response generation module that generates a response to an input document including a plurality of sentences using the graph type knowledge database, the graph type knowledge database including graph data that manages a structure of each of the graph type knowledges, the response generation method comprising: a first step of generating, by the response generation module, a first graph type knowledge from each of the sentences included in the input document; a second step of searching, by the response generation module, a second graph type knowledge similar to each of the plurality of first graph type knowledges while referring to the graph data on the basis of the plurality of first graph type knowledges; a third step of identifying, by the response generation module, the plurality of second graph type knowledges included in a dense location where a density of the plurality of second graph type knowledges is high in a graph space corresponding to the graph type knowledge database as the second graph type knowledges used to generate the response; a fourth step of searching, by the response generation module, third graph type knowledges for generating the response while referring to the graph data on the basis of the identified second graph type knowledges; and a fifth step of generating, by the response generation module, the response using the third graph type knowledges. 7. The response generation method according to claim 6, wherein the third step includes: selecting, by the response generation module, a second graph type knowledge of interest; and identifying, by the response generation module, the dense location where the density of the plurality of second graph type knowledges is high in the graph space on the basis of a distance between the node included in the second graph type knowledge of interest and the node included in each of others of the second graph type knowledges. 8. The response generation method according to claim 7, wherein the third step includes determining, by the response generation module, that the second graph type knowledge of interest is placed in the dense location if the distance is smaller than a threshold. 9. The response generation method according to claim 8, wherein the graph type knowledge database includes attribute data that manages an attribute indicating a condition for making each of the graph type knowledges hold, and the fourth step includes: calculating, by the response generation module, a score indicating consistency, in the condition for making each of the graph type knowledges hold, between each of the identified second graph type knowledges and each of the third graph type knowledges while referring to the attribute data; selecting, by the response generation module, the third graph type knowledge used for generating the response on the basis of the score; and generating, by the response generation module, the response on the basis of the selected third graph type knowledge. 10. The response generation method according to claim 9, wherein the computer holds response type information that defines a type of the response to be output, and the fourth step includes searching, by the response generation module, the third graph type knowledges on the basis of the identified second graph type knowledges and the response type information.