Document Type
Conference Proceeding
Publication Date
6-2008
Abstract
A fundamental problem related to graph structured databases is searching for substructures. One issue with respect to optimizing such searches is the ability to estimate the frequency of substructures within a query graph. In this work, we present and evaluate two techniques for estimating the frequency of subgraphs from a summary of the data graph. In the first technique, we assume that edge occurrences on edge sequences are position independent and summarize only the most informative dependencies. In the second technique, we prune small subgraphs using a valuation scheme that blends information about their importance and estimation power. In both techniques, we assume conditional independence to estimate the frequencies of larger subgraphs. We validate the effectiveness of our techniques through experiments on real and synthetic datasets.
Repository Citation
Maduko, A.,
Anyanwu, K.,
Sheth, A. P.,
& Schliekelman, P.
(2008). Graph Summaries for Subgraph Frequency Estimation. Lecture Notes in Computer Science, 5021, 508-523.
https://corescholar.libraries.wright.edu/knoesis/799
DOI
10.1007/978-3-540-68234-9_38
Included in
Bioinformatics Commons, Communication Technology and New Media Commons, Databases and Information Systems Commons, OS and Networks Commons, Science and Technology Studies Commons
Comments
Presented at the 5th European Semantic Web Conference, Tenerife, Canary Island, Spain, June 1-5, 2008.
The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-540-68234-9_38.