Integration of bottom-up and top-down contextual knowledge in text error correction
Sargur N. Srihari, Jonathan J. Hull, Ramesh Choudhari · 1982
This paper presents an efficient method for the integration of two forms of contextual knowledge into the correction of character substitution errors in words of text: bottom-up knowledge in the form of character transitional probabilities and top-down knowledge in the form of a dictionary. The method is a modification of the Viterbi algorithm---which maximizes string a posteriori probability by using character confusion and transitional probabilities---so that only legal strings are output. The algorithm achieves its efficiency by using a trie structure representation of a dictionary in the search process. An analysis of the computational complexity and the results of experimentation with the approach are presented.