Using zipf frequencies as a representativeness measure in statistical active learning of natural language

Date

2008

Author

Çobanoğlu, Onur

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Active learning has proven to be a successful strategy in quick development of corpora to be used in statistical induction of natural language. A vast majority of studies in this field has concentrated on finding and testing various informativeness measures for samples; however, representativeness measures for samples have not been thoroughly studied. In this thesis, we introduce a novel representativeness measure which is, being based on Zipf's law, model-independent and validated both theoretically and empirically. Experiments conducted on WSJ corpus with a wide-coverage parser show that our representativeness measure leads to better performance than previously introduced representativeness measures when used with most of the known informativeness measures.

Subject Keywords

Computer enginnering., Active learning.

URI

http://etd.lib.metu.edu.tr/upload/3/12609684/index.pdf
https://hdl.handle.net/11511/17685

Collections

Graduate School of Natural and Applied Sciences, Thesis