Evolutionary Language UnderstandingBloomsbury Publishing, 2015 M12 17 - 224 páginas This book records a unique attempt over a ten-year period to use stochastic optimization in the natural language processing domain. Setting the work against the background of the logical rule-based approach, the author provides a context for understanding the differences in assumptions about the nature of language and cognition. |
Contenido
| 1 | |
| 4 | |
3 Simulating Evolution | 30 |
4 An Early System | 53 |
Goals and Standards | 84 |
Front End and Parsing Algorithms | 102 |
Language Model | 129 |
8 Parallel Tree Optimization | 157 |
9 Epilogue | 182 |
References | 187 |
| 193 | |
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accepted algorithm alternative analysis annealing parser annealing run annealing schedule annotation scheme applications APRIL Mk arcs automatic Chomsky clause computational linguistics conditional probabilities configuration containing corpus Correct parse current solution daughter-sequence daughters defined developed elements English example figures Finished at temp freezing criterion full stop function grammatical initial instance labelled trees language model lattice-path logical loop machine microlattice mother label moves natural language natural language processing node labels nonterminal label nonterminal nodes normally noun phrase observed frequencies occur output parsetree parsing path Pathswitch problem processors production programming prototype sequences prototype-set punctuation marks random representing root node Sampson segments sentence simulated annealing skip-and-loop network slave solution space speech statistical stochastic optimization string SUSANNE scheme symbols tagged tagma tagmatags task technique temp Changes terminal nodes theoretical linguistics tion tree structure tree-state Treebank verb group word-hypothesis lattice wordtags