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