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MSTParser is a non-projective dependency parser that searches for maxi
MSTParser is a non-projective dependency parser that searches for maximum spanning trees over directed graphs. Models of dependency structure are based on large-margin discriminative training methods. Projective parsing is also supported.
mstparser 0.5.1 is now available via Maven Central. If you use Maven as your build tool, then you can add it as a dependency in your pom.xml file:
<dependency>
<groupId>net.sourceforge.mstparser</groupId>
<artifactId>mstparser</artifactId>
...
This is an attempt to write a CPU emulator in Trolltech QT 4.4. Basic Functionality: - 8 bit registers - Self-composed instructoin set (in progress) - Data and Assembler Editor / parser (not started) - Text and graphical input / output (not started
Spirit, a different way to write! You guide your mouse through streams of predicted words. As the intelligent agent learns your writing style, its predictions become more accurate. You can prime Spirit with the prose and poetry of any author!
Software to fit whole-sentence language models using the principle of maximum entropy. For developers of speech recognizers, text prediction interfaces, OCR, machine translation software.
This project presents a functional prototype of a new kind of file manager, where the data is auto organized using the semantic content.
The Souvenirs system propose a new complete interface for the user and pretend to remplace the "desktop" paradigm.
A ContextTree is a way of dynamically forming relationships between information: the same information can be viewed in different ways, depending on what you want from it.
The main idea behind this project is the use of a common text to enclose a message by manipulating the structure of the semantic tree of each phrase in the text.