Open Source Java Linguistics Software for Windows

Some software for Corpus Linguistics, which includes Corpus Text Editor, Web-based search, etc. This project created for Belarusian Corpus, but can be used for other languages with some adaption.

WARNING: There are too many false-positives! This is Alpha release, expect many things to improve, including the algorithms. PLEASE GO TO BROWSE ALL FILES TO READ A FULL DESCRIPTION. The goal of this project is simple: Input two sentences of the same language, and obtain the number (from 0 to 1) denoting the similarity between the inputted sentences, according to semantic categories. This project models my previous project: https://sourceforge.net/projects/semantics/ Difference is, this project does not use any database and computes any Strings as an input. JAVA was the language of choice, due to availability of modelling tools. This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by-sa/4.0/. -Powered by WEKA, Classifier4J and SimMetrics.

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.