Spelling correction in the PubMed search engine |
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| Authors: | W John Wilbur Won Kim Natalie Xie |
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| Institution: | (1) National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bldg. 38A, Rm. 6S606, 8600 Rockville Pike, Bethesda, MD 20894, USA |
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| Abstract: | It is known that users of internet search engines often enter queries with misspellings in one or more search terms. Several web search engines make suggestions for correcting misspelled words, but the methods used are proprietary and unpublished to our knowledge. Here we describe the methodology we have developed to perform spelling correction for the PubMed search engine. Our approach is based on the noisy channel model for spelling correction and makes use of statistics harvested from user logs to estimate the probabilities of different types of edits that lead to misspellings. The unique problems encountered in correcting search engine queries are discussed and our solutions are outlined. |
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| Keywords: | Noisy channel model User query logs Nonword error detection Trie Edit distance |
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