文档介绍：ML in NLP June 02
Machine Learning in Natural Introduction
Language Processing
Fernando Pereira
University of Pennsylvania
NASSLLI, June 2002
Thanks to: William Bialek, John Lafferty, Andrew McCallum, Lillian Lee,
Lawrence Saul, Yves Schabes, Stuart Shieber, Naftali Tishby
ML in NLP
Why ML in NLP
Classification
n Examples are easier to create than rules
n Rule writers miss low frequency cases n Document topic
n Many factors involved in language interpretation
n People do it
n AI
n Cognitive science
politics, business national, environment
n Let puter do it
n Moore’s law
n Word sense
n storage
n lots of data treasury bonds ´ chemical bonds
ML in NLP ML in NLP
NASSLI 1
ML in NLP June 02
Analysis
Language Modeling
n Tagging
VBG NNS WDT VBP RP NNS JJ n Is this a likely English sentence?
causing symptoms that show up decades later
P(colorless green ideas sleep furiously)
n Parsing ª 2 ¥105
S(dumped) P(furiously sleep ideas green colorless)
NP-C(workers) VP(dumped)
n
N(workers)V(dumped) NP-C(sacks) PP(into) Disambiguate noisy transcription
It’s easy to wreck a nice beach
workers dumped N(sacks) P(into) NP-C(bin)
It’s easy to recognize speech
sacks into D(a) N(bin)
a bin
ML in NLP ML in NLP
Inference
n Translation Machine Learning Approach
treasury bonds fi obrigações do tesouro
n Algorithms that write programs
covalent bonds fi ligações covalentes
n Specify
n Information extraction • Form of output programs
Sara Lee to Buy 30% of DIM • Accuracy criterion
acquirer Chicago, March 3 - Sara Lee Corp said it agreed to buy a 30 percent interest in n
Paris-based DIM ., a subsidiary of BIC ., at cost of about 20 million Input: set of training examples
acquired dollars. DIM ., a hosiery manufacturer, had sales of about 2 million dollars.
n Output: program that performs as accurately
The investment includes the purchase of 5 million newly issued DIM shares
valued at