Article: Collating Texts Using Progressive Multiple Alignment.

To reconstruct a stemma or do any other kind of statistical analysis of a text tradition, one needs accurate data on the variants occurring at each location in each witness. These data are usually obtained from computer collation programs. Existing programs either collate every witness against a bas...

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Publicado en:Computers & the Humanities Vol. 38; no. 3; pp. 253 - 271
Autores principales: Spencer, Matthew, Howe, Christopher J.
Formato: Artículo
Publicado: Springer Nature Aug2004
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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        10.1007/s10579-004-8682-1
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        atl: Article: Collating Texts Using Progressive Multiple Alignment.
      aug:
        au:
          Spencer, Matthew
          Howe, Christopher J.
        affil:
          Department of Mathematics and Statistics, Dalhousie University, Hal?fax, Nova Scotia, B3H 3J5, Canada.
          Department of Biochemistry, University of Cambridge, Tennis Court Road, Cambridge CB2 JQW, UK.
      su:
        Article (Grammar)
        Statistics
        Algorithms
        Computer software
        Related party transactions
        Mathematics
      sug:
        subj:
          Article (Grammar)
          Statistics
          Algorithms
          Computer software
          Related party transactions
          Mathematics
      keyword:
        dynamic programming
        multiple alignment
        stemma reconstruction
        text collation
        variants
      ab: To reconstruct a stemma or do any other kind of statistical analysis of a text tradition, one needs accurate data on the variants occurring at each location in each witness. These data are usually obtained from computer collation programs. Existing programs either collate every witness against a base text or divide all texts up into segments as long as the longest variant phrase at each point. These methods do not give ideal data for stemma reconstruction. We describe a better collation algorithm (progressive multiple alignment) that collates all witnesses word by word without a base text, adding groups of witnesses one at a time, starting with the most closely related pair.
      pubtype: Academic Journal
      doctype: Article
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    language: English
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