  This paper presents an efficient algorithm for retrieving from a database of
trees, all trees that match a given query tree approximately, that is, within a
certain error tolerance. It has natural language processing applications in
searching for matches in example-based translation systems, and retrieval from
lexical databases containing entries of complex feature structures. The
algorithm has been implemented on SparcStations, and for large randomly
generated synthetic tree databases (some having tens of thousands of trees) it
can associatively search for trees with a small error, in a matter of tenths of
a second to few seconds.
