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Approximate pattern matching is an important computational problem with a wide variety of applications in Information Retrieval. Efficient solutions to approximate pattern matching can be applied to natural language keyword queries with spelling mistakes, OCR scanned text incorporated into indexes, language model ranking algorithms based on term proximity, or DNA databases containing sequencing errors. In this paper, we present a novel approach to constructing text indexes capable ofdoi:10.1145/2407085.2407087 dblp:conf/adcs/PetriC12 fatcat:n5wzkfhvxrhwdmaxr7brmc4xxi