@techreport{citeulike:771872,
	title = {A simple introduction to maximum entropy models for natural language processing},
	author = {A. Ratnaparkhi},
	institution = {nstitute for Research in Cognitive Science, University of Pennsylvania},
	url = {http://citeseer.ist.psu.edu/128751.html},
	year = {1997},
	biburl = {http://www.bibsonomy.org/bibtex/261d3b2424b33e970c306318df9f1ccb6/brightbyte},
	description = {stuff from citeyoulike},
	abstract = {Many problems in natural language processing can be viewed as linguistic classification problems, in which linguistic contexts are used to predict linguistic classes. Maximum entropy models offer a clean way to combine diverse pieces of contextual evidence in order to estimate the probability of a certain linguistic class occurring with a certain linguistic context. This report demonstrates the use of a particular maximum entropy model on an example problem, and then proves some relevant...},
	priority = {2}, citeulike-article-id = {2162753},
	keywords = {nlp statistics }
}