DocumentCode :
2201456
Title :
MDL hierarchical clustering with incomplete data
Author :
Lai, Po-Hsiang ; O´Sullivan, Joseph A.
Author_Institution :
Electr. & Syst. Eng., Washington Univ. in St. Louis, St. Louis, MO, USA
fYear :
2010
fDate :
Jan. 31 2010-Feb. 5 2010
Firstpage :
1
Lastpage :
5
Abstract :
The goal of stemmatology is to reconstruct a family tree of different variants of a text resulting from imperfect copying, which is a crucial part of textual criticism. In reality, historians often have incomplete data because some variants are not yet discovered and there are missing portions in available variants due to physical damage. Stemmatology is similar to molecular phylogenetics where biologists aim to reconstruct the evolutionary history of species based on genetic or protein sequences. Adoption of phylogenetics methods has lead to encouraging results in automatic stemmatology. We discuss and demonstrate the potential application of minimum description length (MDL) concepts to stemmatology. Our method is applied to a realistic dataset and outperforms major existing methods.
Keywords :
pattern clustering; text analysis; MDL hierarchical clustering; genetic sequence; minimum description length; molecular phylogenetics; protein sequence; stemmatology; textual criticism; Bifurcation; Data engineering; Evolution (biology); Genetic mutations; History; Phylogeny; Printing; Proteins; Sequences; Systems engineering and theory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Theory and Applications Workshop (ITA), 2010
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4244-7012-9
Electronic_ISBN :
978-1-4244-7014-3
Type :
conf
DOI :
10.1109/ITA.2010.5454099
Filename :
5454099
Link To Document :
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