Evaluation of model-based retrieval effectiveness with OCR text
ACM Transactions on Information Systems (TOIS)
Phonetic string matching: lessons from information retrieval
SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
Document expansion for speech retrieval
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Applying summarization techniques for term selection in relevance feedback
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Improved string matching under noisy channel conditions
Proceedings of the tenth international conference on Information and knowledge management
The TREC-5 Confusion Track: Comparing Retrieval Methods for Scanned Text
Information Retrieval
Information Retrieval can Cope with Many Errors
Information Retrieval
An Investigation of Mixed-Media Information Retrieval
ECDL '02 Proceedings of the 6th European Conference on Research and Advanced Technology for Digital Libraries
Information Processing and Management: an International Journal
Overview of the CLEF-2005 cross-language speech retrieval track
CLEF'05 Proceedings of the 6th international conference on Cross-Language Evalution Forum: accessing Multilingual Information Repositories
Spoken Content Retrieval: A Survey of Techniques and Technologies
Foundations and Trends in Information Retrieval
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Query expansion is a long standing relevance feedback technique for improving the effectiveness of information retrieval systems. Previous investigations have shown it to be generally effective for electronic text, to give proportionally better improvement for automatic transcriptions of spoken documents, and to be at best of questionable utility for optical character recognized scanned text documents. We introduce two corpus-based methods based on using a string-edit distance measure in context to automatically detect and correct transcription errors. One method operates at query-time and requires no modification of the document index file, and the other at index-time and operates using the standard query-time expansion process. Experimental investigations show these methods to produce improvements in relevance feedback for all three media types, but most significantly mean that relevance feedback can now successfully be applied to scanned text documents.