-
Anglický jazyk
Develop a Part-of-Speech Tagger and a Tagger-Maker
Autor: Jiayun Han
This project is aimed to build an efficient, scalable, portable, and trainable part-of-speech tagger. Using 98% of Penn Treebank-3 as the training data, it builds a raw tagger, using Bayes' theorem, a hidden Markov model, and the Viterbi algorithm. After... Viac o knihe
Na objednávku
36.99 €
bežná cena: 41.10 €
O knihe
This project is aimed to build an efficient, scalable, portable, and trainable part-of-speech tagger. Using 98% of Penn Treebank-3 as the training data, it builds a raw tagger, using Bayes' theorem, a hidden Markov model, and the Viterbi algorithm. After that, a reinforcement machine learning algorithm and contextual transformation rules were applied to increase the tagger's accuracy. The tagger's final accuracy on the testing data is 96.51% and its speed is about 26,000 words per second on a computer with two-gigabyte random access memory and two 3.00 GHz Pentium duo processors. The tagger's portability and trainability are proved by the tagger-maker's success in building a new tagger out of a corpus that is annotated with the tagset different from that of Penn Treebank.
- Vydavateľstvo: LAP LAMBERT Academic Publishing
- Rok vydania: 2013
- Formát: Paperback
- Rozmer: 220 x 150 mm
- Jazyk: Anglický jazyk
- ISBN: 9783659376221
Nemecký jazyk 
