Effective Spell Checking Methods Using Clustering Algorithms

Renato Cordeiro De Amorim, Marcos Zampieri

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    14 Citations (Scopus)
    66 Downloads (Pure)


    This paper presents a novel approach to spell checking using dictionary clustering. The main goal is to reduce the number of times distances have to be calculated when finding target words for misspellings. The method is unsupervised and combines the application of anomalous pattern initialization and partition around medoids (PAM). To evaluate the method, we used an English misspelling list compiled using real examples extracted from the Birkbeck spelling error corpus.
    Original languageEnglish
    Title of host publicationProceedings of Recent Advances in Natural Language Processing
    Subtitle of host publicationRANLP 2013
    EditorsG. Angelova, K. Bontcheva, R. Mitkov
    PublisherAssociation for Computational Linguistics
    ISBN (Print)9781629935553
    Publication statusPublished - 2013
    EventRecent Advances in Natural Language Processing - , Bulgaria
    Duration: 7 Sept 201313 Sept 2013


    ConferenceRecent Advances in Natural Language Processing


    Dive into the research topics of 'Effective Spell Checking Methods Using Clustering Algorithms'. Together they form a unique fingerprint.

    Cite this