%V 8645 %S Lecture Notes in Computer Science %P 74-81 %D 2014 %C Cham, Switzerland %K Phonetic Similarity, String Similarity, Fast Search %N PART 2 %B Database and Expert Systems Applications %T Fast phonetic similarity search over large repositories %X Analysis of unstructured data may be inefficient in the presence of spelling errors. Existing approaches use string similarity methods to search for valid words within a text, with a supporting dictionary. However, they are not rich enough to encode phonetic information to assist the search. In this paper, we present a novel approach for efficiently perform phonetic similarity search over large data sources, that uses a data structure called PhoneticMap to encode language-specific phonetic information. We validate our approach through an experiment over a data set using a Portuguese variant of a well-known repository, to automatically correct words with spelling errors. %I Springer %L discovery10065716 %A H Tissot %A G Peschl %A MD Del Fabro %J Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) %O This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.