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mathematical foundations of computer science homework 1w
Multi-Tagging for Transition-based Dependency Parsing
This project focuses on a modification of a greedy transition based dependency parser. Typically a Part-Of-Speech (POS) tagger models a probability distribution over all the possible tags for each word in the given sentence and chooses one as its best guess. This is then pass on to the parser which uses this information to build a parse tree. The current state of the art for POS tagging is about 97% word accuracy, which seems high but results in a around 56% sentence accuracy. Small errors at the POS tagging phase can lead to large errors down the NLP pipeline and transition based parsers are particularity sensitive to these types of mistakes. A maximum entropy Markov model was trained as a POS multi-tagger passing more than its 1-best guess to the parser which was thought could make a better decision when committing to a parse for the sentence. This has been shown to give improved accuracy in other parsing approaches. We shown there is a correlation between tagging ambiguity and parsers accuracy and in fact the higher the average tags per word the higher the accuracy.
Segurança em Sistemas baseados em Redes de Computadores
This article consists of an analysis of aspects of the care of the security of computer networks, with a strong focus on wireless networks, citing some networking technologies and their pro and cons, as well as elements of defense and security of systems and information that have.
Keywords: systems security, computer networks, wireless, wi-fi security.