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    IPM
    2008
    196views more  IPM 2008»
    Author identification: Using text sampling to handle the class imbalance problem
    13 years 7 months ago
    Author identification: Using text sampling to handle the class imbalance problem
    Download  www.icsd.aegean.gr
    Authorship analysis of electronic texts assists digital forensics and anti-terror investigation. Author identification can be seen as a single-label multi-class text categorizatio...
    Efstathios Stamatatos
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    IJDAR
    2007
    106views more  IJDAR 2007»
    Investigation and modeling of the structure of texting language
    13 years 7 months ago
    Investigation and modeling of the structure of texting language
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    Language usage over computer mediated discourses, like chats, emails and SMS texts, significantly differs from the standard form of the language. An urge towards shorter message l...
    Monojit Choudhury, Rahul Saraf, Vijit Jain, Animes...
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    ACL
    1996
    123views Computational Linguistics» more  ACL 1996»
    The Rhythm of Lexical Stress in Prose
    13 years 8 months ago
    The Rhythm of Lexical Stress in Prose
    Download  web.mit.edu
    \Prose rhythm" is a widely observed but scarcely quanti ed phenomenon. We describe an information-theoretic model for measuring the regularity of lexical stress in English te...
    Doug Beeferman
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    ANLP
    1997
    78views more  ANLP 1997»
    EasyEnglish: A Tool for Improving Document Quality
    13 years 8 months ago
    EasyEnglish: A Tool for Improving Document Quality
    Download  acl.ldc.upenn.edu
    We describe the authoring tool, EasyEnglish, which is part of IBM's internal SGML editing environment, Information Development Workbench. EasyEnglish helps writers produce cl...
    Arendse Bernth
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    ACL
    2003
    119views Computational Linguistics» more  ACL 2003»
    Unsupervised Learning of Arabic Stemming Using a Parallel Corpus
    13 years 8 months ago
    Unsupervised Learning of Arabic Stemming Using a Parallel Corpus
    Download  www.cs.cmu.edu
    This paper presents an unsupervised learning approach to building a non-English (Arabic) stemmer. The stemming model is based on statistical machine translation and it uses an Eng...
    Monica Rogati, J. Scott McCarley, Yiming Yang
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