| 图数据表示与压缩技术综述 |
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| 引用本文： | 张宇,刘燕兵,熊刚,贾焰,刘萍,郭莉.图数据表示与压缩技术综述[J].软件学报,2014,25(9):1937-1952. |
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| 作者姓名： | 张宇 刘燕兵 熊刚 贾焰 刘萍 郭莉 |
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| 作者单位： | 中国科学院 信息工程研究所, 北京 100093;中国科学院大学, 北京 100049;中国科学院 信息工程研究所, 北京 100093;中国科学院 信息工程研究所, 北京 100093;国防科学技术大学 计算机学院, 湖南 长沙 410073;中国科学院 信息工程研究所, 北京 100093;中国科学院 信息工程研究所, 北京 100093 |
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| 基金项目： | 国家自然科学基金(61202477); 国家科技支撑计划(2012BAH46B02); 中国科学院战略性科技先导专项(XDA060 30602) |
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| 摘 要： | 对包含亿万个节点和边的图数据进行高效、紧凑的表示和压缩,是大规模图数据分析处理的基础.图数据压缩技术可以有效地降低图数据的存储空间,同时支持在压缩形式的图数据上进行快速访问.通过深入分析该技术的发展现状,将该技术分为基于传统存储结构的压缩技术、网页图压缩技术、社交网络图压缩技术、面向特定查询的图压缩技术4类.分别对每类技术详细分析了其代表方法并比较了它们之间的性能差异.最后对该技术进行了总结和展望.
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| 关 键 词： | 图数据管理 空间缩减 图数据压缩 网页图 社交网络 |
| 收稿时间： | 2014/1/26 0:00:00 |
| 修稿时间： | 6/9/2014 12:00:00 AM |
Survey on Succinct Representation of Graph Data |
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| ZHANG Yu,LIU Yan-Bing,XIONG Gang,JIA Yan,LIU Ping and GUO Li.Survey on Succinct Representation of Graph Data[J].Journal of Software,2014,25(9):1937-1952. |
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| Authors: | ZHANG Yu LIU Yan-Bing XIONG Gang JIA Yan LIU Ping and GUO Li |
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| Affiliation: | Institute of Information Engineering, The Chinese Academy of Sciences, Beijing 100093, China;University of Chinese Academy of Sciences, Beijing 100049, China;Institute of Information Engineering, The Chinese Academy of Sciences, Beijing 100093, China;Institute of Information Engineering, The Chinese Academy of Sciences, Beijing 100093, China;School of Computer Science, National University of Defense Technology, Changsha 410073, China;Institute of Information Engineering, The Chinese Academy of Sciences, Beijing 100093, China;Institute of Information Engineering, The Chinese Academy of Sciences, Beijing 100093, China |
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| Abstract: | How to effectively compress and represent the large-scale graphic data becomes the fundamental issue for analysis and processing. Graphic data compression technology is an effective solution to significantly reduce the storage space while supporting fast access in the compressed form. An in-depth analysis is provided on the current development of the technologies, including compression technology based on the traditional storage structure, Web graph compression technology, social network compression technology and compression technology for a particular query. A detailed analysis and performance comparison about the representative methods of each technology is presented. Finally, the summary and prospect are listed. |
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| Keywords: | graph data management space reduction graph data compression Web graph social network |
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