On authorship attribution via Markov chains and sequence kernels
We investigate the use of recently proposed character and word sequence kernels for the task of authorship attribution and compare their performance with two probabilistic approaches based on Markov chains of characters and words. Several configurations of the sequence kernels are studied using a relatively large dataset, where each author covered several topics. Utilising Moffat smoothing, the two probabilistic approaches obtain similar performance, which in turn is comparable to that of...[Show more]
|Collections||ANU Research Publications|
|Source:||Proceedings of the 18th International Conference on Pattern Recognition|
|01_Sanderson_On_authorship_attribution_via_2006.pdf||97.58 kB||Adobe PDF||Request a copy|
|02_Sanderson_On_authorship_attribution_via_2006.pdf||166.17 kB||Adobe PDF||Request a copy|
|03_Sanderson_On_authorship_attribution_via_2006.pdf||128.74 kB||Adobe PDF||Request a copy|
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