Browse free open source Linguistics software and projects for Windows below. Use the toggles on the left to filter open source Linguistics software by OS, license, language, programming language, and project status.

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  • 1
    FALCON - Text Search Java Project

    FALCON - Text Search Java Project

    JSON based text search Java Project

    ----------------- - What is it? - ----------------- The "Falcon Search" is a JAVA API and tool to search inside the documents. It was originally started to search the content in pdf files under the project "HAWK Search". Searching with this tool is query-based not word-based as in most of the document search tools OR document readers. It also takes care of jumbling of words within query and spelling mistakes. Commonly used techniques in this project are Natural Language Processing, Information Extraction and Question-Answering Architecture. ---------------------- - Latest Version - ---------------------- Details of latest version can be found on project website - http://geekdadaji.com --------------------------- - CONTACT DETAILS - --------------------------- CREATOR : SWAPNIL A JADHAV (saj1919) EMAIL ID : dadajibudhau@gmail.com WEBSITE : http://geekdadaji.com LICENSE : CC BY-NC 4.0
    Downloads: 0 This Week
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  • 2

    Text Denoising Tool

    Text Denoising Tool removes the insignificant and/or unwanted sentence

    Downloads: 0 This Week
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  • 3
    Text Expander, Inverse summarizer

    Text Expander, Inverse summarizer

    Expand text, inverse summarizer

    IT WILL WORK WITH A JAVA DEVELOPMENT KIT 1.7 ONLY !!! This program is a data-miner and a knowledge-miner. 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. Uncompress the LITE release into a desired directory. 3. Go to a src/ directory with a Terminal/Console/Command-Prompt and do the following: javac Te2.java java Te2 The program should open.
    Downloads: 0 This Week
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  • 4

    TextualModelGenerator

    Generator for textual models by applying different techniques

    This is a project created and supported by: Angel Castellanos Juan Cigarrán Recuero Ana García Serrano This projects allows the modelling of textual contents by applying different techniques: TF-IDF KLD Mutual Information Chi^2 With this application the users can be able to extract the most representative terminology of a textual collection. The application is Java-based, allowing their execution in several platforms and operative systems (Windows, Linux, MacOS).
    Downloads: 0 This Week
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  • 5
    Unsupervised TXT classifier

    Unsupervised TXT classifier

    Classify any two TXT documents, no training required - JAVA

    This program is made to address two most common issues with the known classifying algorithms. First, over-training and second, shortage of data for a training of categories. Instead, each TXT file is a category on its own, rather than an assigned category. In a way, this is similar to clustering but not really a clustering algorithm since there is some training involved. The summarizer from Classifier4J has been adjusted to accept two inputs (lets call them A and B). Then, the summarizer gets trained with A to summarize a document B, and vice versa. This extracts a relevant structure for both documents (and thus avoids the over-training) which are then compared using the Vector-Space analysis to give a range of belonging of one document to another (and thus avoids the shortage of information). This method can be used to create the user-defined classes by merging texts of certain categories and then to calculate the relevant distances between the documents, but this is not necessary.
    Downloads: 0 This Week
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