On Correcting Misspelled Queries in Email Search

Abhijit Bhole, Raghavendra Udupa
2015 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
We consider the problem of providing spelling corrections for misspelled queries in Email Search using user's own mail data. A popular strategy for general query spelling correction is to generate corrections from query logs. However, this strategy is not effective in Email Search for two reasons: 1) query log of any sin- gle user is typically not rich enough to provide potential corrections for a new query 2) corrections generated us- ing query logs of other users are not particularly useful
more » ... nce the mail data as well as search intent are highly specific to the user. We address the challenge of design- ing an effective spelling correction algorithm for Email Search in the absence of query logs. We propose SpEQ, a Machine Learning based approach that generates cor- rections for misspelled queries directly from the user's own mail data.
doi:10.1609/aaai.v29i1.9282 fatcat:da6iqbmtqrb7te5lpskqvpc66y