@article{oai:repository.nii.ac.jp:00000331,
 author = {市瀬, 龍太郎 and Ichise, Ryutaro and 武田, 英明 and Takeda, Hideaki and 本位田, 真一 and Honiden, Shinichi},
 journal = {NIIテクニカル・レポート, NII Technical Report},
 month = {May},
 note = {Hierarchical categorization is a powerful and convenient method so that it is commonly used in various areas, for example ontologies and information categorization. Although each hierarchy is useful, there are problems to manage multiple hierarchies. In this paper, we propose an alignment method between concept hierarchies by using a statistical method. By using this method, a concept that exists in one hierarchy system but does not in the other can be located in a suitable position in the other. The key idea is to find similar categories between two systems to be able to transfer concepts from one system to the other. Similarity is measured by "k(kappa) statistic" based on instances belonging categories. The experiments of our method with concept hierarchies of Yahoo! and LYCOS result over 80% of accuracy to estimate appropriate positions of concepts between two hierarchies.},
 pages = {1--9},
 title = {NII Technical Report (NII-2001-001E)：An Alignment Algorithm between Concept Hierarchies},
 year = {2001}
}