Characterizing Similarity Structure of Spatial Networks Based on Degree Mixing Patterns

• Item type: National Convention(1)
• 公開日: 2016-03-10
• タイトル: Characterizing Similarity Structure of Spatial Networks Based on Degree Mixing Patterns
• 言語: eng
• キーワード / 主題Scheme: Other
• キーワード / 主題: 人工知能と認知科学
• 資源タイプ / 資源タイプ識別子: http://purl.org/coar/resource_type/c_5794
• 資源タイプ: conference paper
• 著者所属: 静岡県大
• 著者所属: 静岡県大
• 著者所属: 静岡県大
• 著者所属: 静岡県大
• 著者所属: 静岡県大
• 著者所属: 静岡県大
• 著者所属: 静岡県大
• 著者名: アリフ, マウラナ; 斉藤, 和巳; 池田, 哲夫; 湯瀬, 裕明; 渡邉, 貴之; 大久保, 誠也; 武藤, 伸明
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: We address a problem of classifying and characterizing spatial networks in terms of local connection patterns of node degrees, by especially focusing on the property that the maximum node degrees of these networks are restricted to relatively small numbers. To this end, we propose two methods to analyze a set of such networks by 1) enumerating and counting the combinations of node degrees with respect to connected pair or triple nodes, 2) calculating feature vectors of these networks, which express distributions of mixing patterns' Z scores, and 3) constructing a dendrogram of these networks based on a cosine similarity between these feature vectors. In our experiments using spatial networks constructed from urban streets of seventeen cities, we confirm that our method can produce intuitively interpretable results which reflect regional characteristics of these cities. Moreover, we show that these characteristics can be reasonably described in terms of a relatively small number of selected mixing patterns, as main building blocks of given spatial networks.
• 書誌レコードID / 収録物識別子タイプ: NCID
• 書誌レコードID / 収録物識別子: AN00349328
• 書誌情報: 第78回全国大会講演論文集; 巻 2016, 号 1, p. 611-612, 発行日 2016-03-10
• 出版者 / 言語: ja
• 出版者: 情報処理学会