@inproceedings{discovery10065716,
           title = {Fast phonetic similarity search over large repositories},
          number = {PART 2},
          volume = {8645},
            year = {2014},
          series = {Lecture Notes in Computer Science},
           pages = {74--81},
         journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
           month = {January},
         address = {Cham, Switzerland},
       booktitle = {Database and Expert Systems Applications},
       publisher = {Springer},
            note = {This version is the author accepted manuscript. For information on re-use, please refer to the publisher's terms and conditions.},
        abstract = {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.},
             url = {https://doi.org/10.1007/978-3-319-10085-2\%5f6},
          author = {Tissot, H and Peschl, G and Del Fabro, MD},
        keywords = {Phonetic Similarity, String Similarity, Fast Search},
            issn = {1611-3349}
}