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Bell-LaPadula model - original papers


 
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Old 12-18-2008
Bell-LaPadula model - original papers

Going back, well, almost to the beginning:

A reconstruction of the first part of the famous Bell-LaPadula (BLP) model.  Note that this is a formal mathematical model, using symbolic logic.  Not the first formal model of security, nor even the first state machine model, but one of the most useful in the early days.

The second part of the famous Bell-LaPadula model is available here.

So, now you know.

Possibly easier to follow, a review of the Bell-LaPadula model, thirty years later, by David Bell.

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apertium-lextor(1)														apertium-lextor(1)

NAME
apertium-lextor - This application is part of ( apertium ) This tool is part of the apertium machine translation architecture: http://apertium.org. SYNOPSIS
apertium-lextor --trainwrd stopwords words n left right corpus model [ --weightexp w ] [ --debug ] apertium-lextor --trainlch stopwords lexchoices n left right corpus wordmodel dic bildic model [ --weightexp w ] [ --debug ] apertium-lextor --lextor model dic left right [ --debug ] [ --weightexp w ] DESCRIPTION
apertium-lextor is the application responsible for training and usage of the lexical selector module. OPTIONS
--trainwrd | -t Train word co-occurrences model. It needs the following required parameters: stopwords file containing a list of stop words. Stop words are ignored. words file containing a list of words. For each word a co-occurrence model is built. n number of words per co-occurrence model (for each model, the n most frequent words). left left-side context to take into account (number of words). right right-side context to take into account (number of words). corpus file containing the training corpus. model output file on which the co-occurrence models are saved. --trainlch | -r Train lexical choices co-occurrence models using a target language co-occurrence model and a bilingual dictionary. It needs the following required parameters: stopwords file containing a list of stop words. Stop words are ignored. lexchoices file containing a list of lexical choices. For each lexical choice a co-occurrence model is built. n number of words per co-occurrence model (for each model, the n most frequent words). left left-side context to take into account (number of words). right right-side context to take into account (number of words). corpus file containing the training corpus. wordmodel target-language word co-occurrence model (previously trained by means of the --trainwrd option). dic the lexical-selection dictionary (binary format). bildic the bilingual dictionary (binary format). model output file on which the co-occurrence models are saved. --lextor | -l Perform the lexical selection on the input stream. It needs the following required parameters: model file containing the model to be used for the lexical selection. dic lexical-selection dictionary (binary format). left left-side context to take into account (number of words). right right-side context to take into account (number of words). --weightexp w Specify a weight value to change the influence of surrounding words while training or performing the lexical selection. The parameter w must be a positive value. --debug | -d Show debug information while working. --help | -h Shows this help. --version | -v Shows license information. SEE ALSO
apertium-gen-lextorbil(1), apertium-preprocess-corpus-lextor(1), apertium-gen-stopwords-lextor(1), apertium-gen-wlist-lextor(1), aper- tium-gen-wlist-lextor-translation(1), apertium-lextor-eval(1), apertium-lextor-mono(1). BUGS
Lots of...lurking in the dark and waiting for you! AUTHOR
(c) 2005,2006 Universitat d'Alacant / Universidad de Alicante. All rights reserved. 2006-12-12 apertium-lextor(1)