Hashing Tree-Structured Data: Methods and Applications

被引:19
作者
Tatikonda, Shirish [1 ]
Parthasarathy, Srinivasan [1 ]
机构
[1] Ohio State Univ, Dept Comp Sci & Engn, Columbus, OH 43202 USA
来源
26TH INTERNATIONAL CONFERENCE ON DATA ENGINEERING ICDE 2010 | 2010年
基金
美国国家科学基金会;
关键词
LARGEST COMMON SUBTREES; EDITING DISTANCE; ALGORITHMS;
D O I
10.1109/ICDE.2010.5447882
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
In this article we propose a new hashing framework for tree-structured data. Our method maps an unordered tree into a multiset of simple wedge-shaped structures refered to as pivots. By coupling our pivot multisets with the idea of minwise hashing, we realize a fixed sized signature-sketch of the tree-structured datum yielding an effective mechanism for hashing such data. We discuss several potential pivot structures and study some of the theoretical properties of such structures, and discuss their implications to tree edit distance and properties related to perfect hashing. We then empirically demonstrate the efficacy and efficiency of the overall approach on a range of real-world datasets and applications.
引用
收藏
页码:429 / 440
页数:12
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