Answering pattern match queries in large graph databases via graph embedding

Answering pattern match queries in large graph databases via graph embedding The growing popularity of graph databases has generated interesting data management problems, such as subgraph search, shortest path query, reachability verification, and pattern matching. Among these, a pattern match query is more flexible compared with a subgraph search and more informative compared with a shortest path or a reachability query. In this paper, we address distance-based pattern match queries over a large data graph G . Due to the huge search space, we adopt a filter-and-refine framework to answer a pattern match query over a large graph. We first find a set of candidate matches by a graph embedding technique and then evaluate these to find the exact matches. Extensive experiments confirm the superiority of our method. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The VLDB Journal Springer Journals

Answering pattern match queries in large graph databases via graph embedding

Loading next page...
 
/lp/springer_journal/answering-pattern-match-queries-in-large-graph-databases-via-graph-3SDmNRKZJm
Publisher
Springer-Verlag
Copyright
Copyright © 2012 by Springer-Verlag
Subject
Computer Science; Database Management
ISSN
1066-8888
eISSN
0949-877X
D.O.I.
10.1007/s00778-011-0238-6
Publisher site
See Article on Publisher Site

Abstract

The growing popularity of graph databases has generated interesting data management problems, such as subgraph search, shortest path query, reachability verification, and pattern matching. Among these, a pattern match query is more flexible compared with a subgraph search and more informative compared with a shortest path or a reachability query. In this paper, we address distance-based pattern match queries over a large data graph G . Due to the huge search space, we adopt a filter-and-refine framework to answer a pattern match query over a large graph. We first find a set of candidate matches by a graph embedding technique and then evaluate these to find the exact matches. Extensive experiments confirm the superiority of our method.

Journal

The VLDB JournalSpringer Journals

Published: Feb 1, 2012

References

  • Saga: a subgraph matching tool for biological graphs
    Tian, Y.; McEachin, R.C.; Santos, C.; States, D.J.; Patel, J.M.

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 12 million articles from more than
10,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Unlimited reading

Read as many articles as you need. Full articles with original layout, charts and figures. Read online, from anywhere.

Stay up to date

Keep up with your field with Personalized Recommendations and Follow Journals to get automatic updates.

Organize your research

It’s easy to organize your research with our built-in tools.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve Freelancer

DeepDyve Pro

Price
FREE
$49/month

$360/year
Save searches from
Google Scholar,
PubMed
Create lists to
organize your research
Export lists, citations
Read DeepDyve articles
Abstract access only
Unlimited access to over
18 million full-text articles
Print
20 pages/month
PDF Discount
20% off