4 projects for "python text parser" with 2 filters applied:

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  • 1

    Arabic Corpus

    Text categorization, arabic language processing, language modeling

    The Arabic Corpus {compiled by Dr. Mourad Abbas ( http://sites.google.com/site/mouradabbas9/corpora ) The corpus Khaleej-2004 contains 5690 documents. It is divided to 4 topics (categories). The corpus Watan-2004 contains 20291 documents organized in 6 topics (categories). Researchers who use these two corpora would mention the two main references: (1) For Watan-2004 corpus ---------------------- M. Abbas, K. Smaili, D. Berkani, (2011) Evaluation of Topic Identification Methods on...
    Downloads: 11 This Week
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  • 2

    Presage

    the intelligent predictive text entry platform

    Presage (formerly Soothsayer) is an intelligent predictive text entry system. Presage generates predictions by modelling natural language as a combination of redundant information sources. Presage computes probabilities for words which are most likely to be entered next by merging predictions generated by the different predictive algorithms. Presage's modular and extensible architecture allows its language model to be extended and customized to utilize statistical, syntactic, and semantic...
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    Downloads: 311 This Week
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  • 3

    mwetoolkit

    THIS PROJECT MIGRATED TO https://gitlab.com/mwetoolkit/mwetoolkit3/

    THIS PROJECT MIGRATED TO https://gitlab.com/mwetoolkit/mwetoolkit3/ The Multiword Expressions toolkit aids in the automatic identification and extraction of multiword units in running text. These include idioms (kick the bucket), noun compounds (cable car), phrasal verbs (take off, give up), etc. Even though it focuses on multiword expresisons, the framework is quite complete and can also be useful in any corpus-based study in computational linguistics. The mwetoolkit can be applied to virtually any text collection, language, and MWE type. ...
    Downloads: 1 This Week
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  • 4
    AsiEs stands for Asistente de Escritura (writing assistant). It provides word prediction and autocomplete for fast writing. Thought for people with difficulties writing on keyboard, improves the writing speed preventing the user from pressing at most 50% of keys to write and avoids ortographic errors. Made by Fundación Teletón Uruguay (http://www.teleton.org.uy/home/)
    Downloads: 0 This Week
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