Open Source Linux Information Analysis Software - Page 8

Task of the project is a semantic annotation of Czech texts by using NLP tools.

** IMPORTANT NOTICE ** 10 Feb 2006 Code is being moved to the SMI subversion repository (http://smi-protege.stanford.edu/svn/owl/trunk/) Project will continue to be open source. ProtegeOWL info at: http://protege.stanford.edu/overview/protege-owl.html

SENTENSA Knowledge Miner is a platform independent tool for searching any text. SENTENSA uses robust methods of indexing and searching text, leveraging on experience from more than 20 years of information retrieval.

Siafu simulates individual agents and their context, from home to city-wide scenarios. As a developer, you use the API to write your simulation for the purposes of data-set generation, test or visualization, optionally hooking it to your own application.

SNARLI (Simple Neural ARchitecture LIbrary) is a Java package containing a back-prop layer class and classes for the Self-Organizing Map and Incremental Growing Grid. The back-prop class supports sigma-pi connections and back-prop-through-time.

This project consists in a simulation software of robot A.I. It is aimed at comparing the efficiency of robot intelligence against movement tasks between fixed checkpoints in a logical world.

Design and develop Recommendation and Adaptive Prediction Engines to address eCommerce opportunities. Build a portfolio of engines by creating and porting algorithms from multiple disciplines to a usable form. Try to solve NetFlix and other challenges.

The software annotates text with 41 broad semantic categories (Wordnet supersenses) for both nouns and verbs; i.e., it performs both sense disambiguation and named-entity recognition. The tagger implements a discriminatively-trained Hidden Markov Model.

The Toolkit for Advanced Discriminative Modeling (TADM) is a C++ implementation for estimating the parameters of discriminative models, such as maximum entropy models. It uses the PETSc and TAO toolkits to provide high performance and scalability.

TBLTools is a set of GATE processing resources that implements the Fast Transformation Based Learning Algorithm. You can train it to learn rules for NLP tasks such as Named Entity Recognition and Shallow parsing.

TIKAPP is becoming a collection of tools for simulation of neural networks. The first available part is an ANSI-C++ library with support for backpropation networks.

The Text Annotation Environment (tae) can be used to annotate natural language text manually or automatically (UIMA Annotator) with meta information (tokens, part-of-speech, named entities, ...). Tae is based on Eclipse and IBM's UIMA.

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.

Text Matrix implements a c++ library and corresponding utilities for text mining. Cross-platform execution are supported.

TextMine is for the Perl hacker who is grappling with the problems of managing unstructured text from various sources. You can use these text mining tools to search the Web, index text, extract entities, categorize your e-mail, and summarize documents.

The Thot toolkit repository has moved to http://daormar.github.io/thot/ Thot is a toolkit for statistical machine translation. The new Thot toolkit includes fully automatic and interactive machine translation, incremental training of statistical models, parallel estimation, ...

TimeSleuth discovers temporal decision rules. It also judges the (a)causality of the rules. TimeSleuth can discover rules that involve time: {if (rainy_yesterday = true) then rainy_today = true}, or {if (rainy_tomorrow = true) then rainy_today = true}.

This project is a compilation of tools/libraries to help with tasks related to Text Analytics mainly in Java. These tools range from simple wrappers to sophisticated mining tasks that can improve the productivity of researchers and engineers.

T-Rex (Trainable Relation Extraction) is a highly configurable machine learning-based Information Extraction from Text framework, which includes tools for document classification, entity extraction and relation extraction.

The TreeQ package is a set of C-language applications that implement a automatic machine learning algorithm based on a tree-structured classifier. This approach is particularly effective for high-dimensional continuous data such as audio and video.

It gives facility of collecting tweets through Twitter Streaming API w.r.t different search criteria and to save tweets in CSV and ARFF (WEKA) file formats.

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.

Uranie is a sensitivity and uncertainty analysis plateform based on the ROOT framework (http://root.cern.ch) . It is developed at CEA, the French Atomic Energy Commission (http://www.cea.fr). It provides various tools for: - data analysis - sampling - statistical modeling - optimisation - sensitivity analysis - uncertainty analysis - running code on high performance computers - etc. Thanks to ROOT, it is easily scriptable in CINT (c++ like syntax) and Python. Is is available both for Unix and Windows platforms (a dedicated platform archive is available on request). Note : if you have downloaded version 3.12 before the 8th of february, a patch exists for a minor bug on TOutputFileKey file, don't hesitate to ask us.

Reimplementation of the anomaly detection/one-class classification algorithm 'V-detector'.

VDM.net So how can I call you My Dear Project?