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Swordfish: an unsupervised Ngram based approach to morphological analysis

Published: 06 August 2006 Publication History

Abstract

Extracting morphemes from words is a nontrivial task. Rule based stemming approaches such as Porter's algorithm have encountered some success, however they are restricted by their ability to identify a limited number of affixes and are language dependent. When dealing with languages with many affixes, rule based approaches generally require many more rules to deal with all the possible word forms. Deriving these rules requires a larger effort on the part of linguists and in some instances can be simply impractical. We propose an unsupervised ngram based approach, named Swordfish. Using ngram probabilities in the corpus, possible morphemes are identified. We look at two possible methods for identifying candidate morphemes, one using joint probabilities between two ngrams, and the second based on log odds between prefix probabilities. Initial results indicate the joint probability approach to be better for English while the prefix ratio approach is better for Finnish and Turkish.

References

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Baeza-Yates R. and Ribeiro-Neto B.: Modern Information Retrieval. Addison-Wesley 1999.
[2]
Creutz M. and Lagus K.: Unsupervised Morpheme Segmentation and Morphology Induction from Text Corpora Using Morfessor 1.0. Tech. rep. A81, Helsinki University of Technology, 2005.
[3]
Goldsmith J.: Unsupervised learning of the morphology of a natural language. Comput. Linguist. 27 (2). 2001. 153--198
[4]
Unsupervised Segmentation of Words into Morphemes Challenge 2005. www.cis.hut.fi/morphochallenge2005.
[5]
Yamamoto M. and Church K.W.: Using suffix arrays to compute term frequency and document frequency for all substrings in a corpus. Comput. Linguist. 27 (1). 2001. 1--30

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  1. Swordfish: an unsupervised Ngram based approach to morphological analysis

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    cover image ACM Conferences
    SIGIR '06: Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
    August 2006
    768 pages
    ISBN:1595933697
    DOI:10.1145/1148170
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    New York, NY, United States

    Publication History

    Published: 06 August 2006

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    1. Ngrams
    2. morphemes

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    SIGIR06
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    SIGIR06: The 29th Annual International SIGIR Conference
    August 6 - 11, 2006
    Washington, Seattle, USA

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    Overall Acceptance Rate 792 of 3,983 submissions, 20%

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