A general algorithm for subtree similarity-search

Sara Cohen, Nerya Or

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

10 Scopus citations


Determining similarity between trees is an important problem in a variety of areas. The subtree similarity-search problem is that of finding, given a tree Q and a large set of trees Γ = (T1;...; Tn), the subtrees of trees among Γ that are most similar to Q. Similarity is defined using some tree distance function. While subtree similarity-search has been studied in the past, solutions mostly focused on specific tree distance functions, and were usually applicable only to ordered trees. This paper presents an efficient new algorithm that solves the subtree similarity-search problem, and is compatible with a wide family of tree distance functions (for both ordered and unordered trees). Extensive experimentation confirms the efficiency and scalability of the algorithm, which displays consistently good runtime even for large queries and datasets.

Original languageAmerican English
Title of host publication2014 IEEE 30th International Conference on Data Engineering, ICDE 2014
PublisherIEEE Computer Society
Number of pages12
ISBN (Print)9781479925544
StatePublished - 2014
Event30th IEEE International Conference on Data Engineering, ICDE 2014 - Chicago, IL, United States
Duration: 31 Mar 20144 Apr 2014

Publication series

NameProceedings - International Conference on Data Engineering
ISSN (Print)1084-4627


Conference30th IEEE International Conference on Data Engineering, ICDE 2014
Country/TerritoryUnited States
CityChicago, IL


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