@article{oai:nagoya.repo.nii.ac.jp:00018612,
 author = {小林, 大輔 and 吉川, 大弘 and 古橋, 武 and KOBAYASHI, Daisuke and YOSHIKAWA, Tomohiro and FURUHASHI, Takeshi},
 issue = {2},
 journal = {日本感性工学会論文誌},
 month = {Mar},
 note = {A lot of companies carry out questionnaires, which often have questions that can be answered by free-form text. However, it is time-consuming to get the outline of all responses by reading the whole text, and it is difficult to analyze them without subjective bias. The authors have proposed “HK Graph” (Hierarchical Keyword Graph), which is a support tool for text mining. HK Graph visualizes the relationship among words with a hierarchical graph structure. However, the conventional HK Graph shows words and their synonyms; consequently, the visualization gets complicated. This paper proposes a new HK Graph, in which synonyms are aggregated using a thesaurus. The experimental results showed that synonyms were appropriately aggregated while the amount of intrinsic information in the visualized result was increased. As a result, it became easier to grasp the outline in the proposed HK Graph than in the conventional HK Graph.},
 pages = {159--165},
 title = {概念を用いたHK Graphによるテキスト解析支援},
 volume = {11},
 year = {2012}
}