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Konferenzbeitrag

Combining Text and Linguistic Document Representations for Authorship Attribution

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons44741

Kaster,  Andreas
Databases and Information Systems, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons45482

Siersdorfer,  Stefan
Databases and Information Systems, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons45720

Weikum,  Gerhard
Databases and Information Systems, MPI for Informatics, Max Planck Society;

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Zitation

Kaster, A., Siersdorfer, S., & Weikum, G. (2005). Combining Text and Linguistic Document Representations for Authorship Attribution. In Workshop Stylistic Analysis of Text for Information Access, 28th International SIGIR (pp. 27-35). Saarbrücken, Germany: MPI.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-000F-260F-D
Zusammenfassung
In this paper, we provide several alternatives to the classical Bag-Of-Words model for automatic authorship attribution. To this end, we consider linguistic and writing style infor- mation such as grammatical structures to construct di®er- ent document representations. Furthermore we describe two techniques to combine the obtained representations: combi- nation vectors and ensemble based meta classi¯cation. Our experiments show the viability of our approach.