Results of Applying Probabilistic IR to OCR Text
Seventeenth Annual International ACM-SIGIR Conference on Research and Development in Information Retrieval
Character accuracy of optically recognized text is considered a basic measure for evaluating OCR devices. In the broader sense, another fundamental measure of an OCR’s goodness is whether its generated text is usable for retrieving information. In this study, we evaluate retrieval effectiveness from OCR text databases using a probabilistic IR system. We compare these retrieval results to their manually corrected equivalent. We show there is no statistical difference in precision and recall using graded accuracy levels from three OCR devices. However, characteristics of the OCR data have side effects that could cause unstable results with this IR model. In particular, we found individual queries can be greatly affected. Knowing the qualities of OCR text, we compensate for them by applying an automatic post-processing system that improves effectiveness.
Information retrieval; Optical character recognition; Optical character recognition devices – Evaluation; Optical pattern recognition
Computer Engineering | Computer Sciences | Electrical and Computer Engineering | Hardware Systems | Library and Information Science | Software Engineering
Use Find in Your Library, contact the author, or interlibrary loan to garner a copy of the item. Publisher policy does not allow archiving the final published version. If a post-print (author's peer-reviewed manuscript) is allowed and available, or publisher policy changes, the item will be deposited.
Results of Applying Probabilistic IR to OCR Text.
Presentation at Seventeenth Annual International ACM-SIGIR Conference on Research and Development in Information Retrieval,
Available at: http://digitalscholarship.unlv.edu/ece_presentations/36