Retrieval methods for English-text with misrecognized OCR characters

This paper presents three probabilistic text retrieval methods designed to carry out a full-text search of English documents containing OCR errors. By searching for any query term on the premise that there are errors in the recognized text, the methods presented can tolerate such errors, and therefore costly manual postediting is trot required after OCR recognition. In the applied approach, confusion matrices are used to store characters which are likely to be interchanged when a particular character is missrecognized, and the respective probability of each occurrence. Moreover, a 2-gram matrix is used to store probabilities of character connection, i.e., which letter is likely to come after another. Multiple search terms are generated far an input query term by making reference to confusion matrices, after which a full-text search is run far each search term, The validity of retrieved terms is determined based on error-occurrence and character-connection probabilities. The performance of these methods is experimentally evaluated by determining retrieval effectiveness, i.e., by calculating recall and precision rates. Results indicate marked improvement in comparison with exact matching.