Efficient best-first dictionary search given graph-based input

This paper describes a novel method for applying dictionary knowledge to optimally interpret the confidence-rated hypothesis sets produced by lower-level pattern classifiers. The problem is cast as enumerating the paths in a graph in best-first order given the constraint that each complete path is a word in some specified dictionary. The solution described here is of particular interest due to its generality, flexibility and because the time to retrieve each path is independent of the size of the dictionary. Results are presented for searching dictionaries of up to 1 million UK postcodes given graphs that correspond to insertion, deletion and substitution errors