Showing 9 open source projects for "process"

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  • 1

    RDRPOSTagger

    A Rule-based Part-of-Speech and Morphological Tagging Toolkit

    RDRPOSTagger is a robust, easy-to-use and language-independent rule-based toolkit for Part-of-Speech (POS) and morphological tagging. RDRPOSTagger obtains fast performance in both learning and tagging process. RDRPOSTagger also achieves a very competitive accuracy in comparison to the state-of-the-art results. RDRPOSTagger now supports pre-trained POS and morphological tagging models for Bulgarian, Czech, Dutch, English, French, German, Hindi, Italian, Portuguese, Spanish, Swedish, Thai and Vietnamese. Additionally, RDRPOSTagger supports the pre-trained Universal POS tagging models for 40 languages. ...
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  • 2

    BioC

    We describe a simple XML format to share text documents and annotation

    ... - BioC-formatted corpora - BioC tools that work with BioC corpora BioC goals - simplicity - interoperability - broad use - reuse There should be little investment required to learn to use a format or a software module to process that format. We are interested in reuse, and we focus on common NLP tasks that are broadly useful for textmining.
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  • 3
    Phrasal

    Phrasal

    Statistical phrase-based machine translation system

    ...Developed by The Natural Language Processing Group at Stanford University, a team of faculty, postdocs, programmers and students who work together on algorithms that allow computers to process and understand human languages. Our work ranges from basic research in computational linguistics to key applications in human language technology, and covers areas such as sentence understanding, automatic question answering, machine translation, syntactic parsing and tagging, sentiment analysis.
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  • 4
    Stemmer Gujarati

    Stemmer Gujarati

    Offline stemmer for Gujarati , which is one of 22 Indian languages.

    This is a Gujarati stemmer in Java. Stemming is a process in which affixes are removed form the root word (stem). It relates morphological variant words to corresponding common root. For example "પ્રતિઉપયોગી" is word which has stem " ઉપયોગ". Stemmers are language specific tools. The design of a stemming algorithm requires a significant level of linguistic expertise. There has been lot of significant work in the development and evaluation of stemmer for non-Indian languages, but very less or no significant work has been done on Indian front especially for Gujarati language.The code of this stemmer is based on algorithm designed under guidance of Prof. ...
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  • 5
    Text Expander, Inverse summarizer

    Text Expander, Inverse summarizer

    Expand text, inverse summarizer

    ...It does exactly the opposite of what the text summarizers do. A text summarizer produces a shortened text given some text as an input. An inverse summarizer takes the shortened input, a similar or a same text and does the process in reverse. This results in an expanded text. It can be used with any text or notes that have the knowledge gaps. It is a great aid to any creative work and it simply pin-points to data that may be of some relevance. How to run this program? 1. Make sure JAVA 1.7 development is installed and running/compiling properly with all environment variables properly set. 2. ...
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  • 6
    EyeMap - Eye Movement Data Analyzer
    EyeMap is a visualization and analysis tool for text reading eye movement data. It can process Unicode, proportion/non-proportion and spaced/unspaced reading materials, which supports various languages and experiment methods.
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  • 7
    openTMS is a free, open source, translation memory system based entirely on open-source standards.
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  • 8

    Wordcorr

    Data management for comparative linguistics

    Wordcorr automates the tedious and risky process of tabulating and managing the sound correspondences used in working out the historical development of natural languages. Initial support was from NSF.
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  • 9

    Supertagger

    Software for assigning supertags.

    Supertagging is a process of statistical lexical disambiguation, preprocessing step to parsing, which assigns LTAG tree categories to the lexical items present in the input sentence. Thus, if the input sentence is in the form of a dependency tree, the task of the supertagger is to assign the most probable TAG family to each node and edge in the dependency tree.
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