  Many web databases can be seen as providing partial and overlapping
information about entities in the world. To answer queries effectively, we need
to integrate the information about the individual entities that are fragmented
over multiple sources. At first blush this is just the inverse of traditional
database normalization problem - rather than go from a universal relation to
normalized tables, we want to reconstruct the universal relation given the
tables (sources). The standard way of reconstructing the entities will involve
joining the tables. Unfortunately, because of the autonomous and decentralized
way in which the sources are populated, they often do not have Primary Key -
Foreign Key relations. While tables may share attributes, naive joins over
these shared attributes can result in reconstruction of many spurious entities
thus seriously compromising precision. Our system, \smartint\ is aimed at
addressing the problem of data integration in such scenarios. Given a query,
our system uses the Approximate Functional Dependencies (AFDs) to piece
together a tree of relevant tables to answer it. The result tuples produced by
our system are able to strike a favorable balance between precision and recall.
