@techreport{TD:100486,
	att_abstract={{Increasingly complex databases need ever more sophisticated tools 
to help users understand their schemas and interact with the data. 
Existing tools fall short of either providing the ``big picture,'' 
or of presenting useful connectivity information.

In this paper we define summary graphs, a novel approach for
summarizing schemas. Given a set of user-specified query tables,
the summary graph automatically computes the most relevant tables
and joins for that query set.  The output preserves the most
informative join paths between the query tables, while meeting
size constraints. In the process, we define a novel
information-theoretic measure over join edges. Unlike most
subgraph extraction work, we allow metaedges (i.e., edges in the
transitive closure) to help reduce output complexity. We prove
that the problem is NP-Hard, and solve it as an integer program.
Our extensive experimental study shows that our method returns
high-quality summaries under independent quality measures.}},
	att_authors={cp2838, ds8961},
	att_categories={},
	att_copyright={{VLDB Foundation}},
	att_copyright_notice={{The definitive version was published in Very Large Databases, 2011. {{, 2011-08-29}}
}},
	att_donotupload={},
	att_private={false},
	att_projects={},
	att_tags={},
	att_techdoc={true},
	att_techdoc_key={TD:100486},
	att_url={http://web1.research.att.com:81/techdocs_downloads/TD:100486_DS1_2011-09-04T18:55:18.227Z.pdf},
	author={Cecilia Procopiuc and Divesh Srivastava and Xiaoyan Yang},
	institution={{VLDB Conference}},
	month={August},
	title={{Summary Graphs for Relational Database Schemas}},
	year=2011,
}