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A Modern C++ Data Sciences Toolkit
| Date | Stars |
|---|---|
| 2026-07-24 | 714 |
| 2026-07-25 | 714 |
| 2026-07-28 | 714 |
| 2026-07-30 | 714 |
| 2026-08-06 | 714 |
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# MeTA: ModErn Text Analysis
Please visit our [web page][meta-website] for information and tutorials
about MeTA!
### Build Status (by branch)
- master: [](https://travis-ci.org/meta-toolkit/meta)
[](https://ci.appveyor.com/project/skystrife/meta)
- develop: [](https://travis-ci.org/meta-toolkit/meta)
[](https://ci.appveyor.com/project/skystrife/meta)
# Outline
- [Intro](#intro)
- [Documentation](#documentation)
- [Tutorials](#tutorials)
- [Citing](#citing)
- [Project Setup](#project-setup)
- [Mac OS X](#mac-os-x-build-guide)
- [Ubuntu](#ubuntu-build-guide)
- [Arch Linux](#arch-linux-build-guide)
- [Fedora](#fedora-build-guide)
- [CentOS](#centos-build-guide)
- [EWS/EngrIT](#ewsengrit-build-guide) (this is UIUC-specific)
- [Windows](#windows-build-guide)
- [Generic Setup Notes](#generic-setup-notes)
# Intro
MeTA is a modern C++ data sciences toolkit featuring
- text tokenization, including deep semantic features like parse trees
- inverted and forward indexes with compression and various caching strategies
- a collection of ranking functions for searching the indexes
- topic models
- classification algorithms
- graph algorithms
- language models
- CRF implementation (POS-tagging, shallow parsing)
- wrappers for liblinear and libsvm (including libsvm dataset parsers)
- UTF8 support for analysis on various languages
- multithreaded algorithms
## Documentation
Doxygen documentation can be found [here][doxygen].
## Tutorials
We have walkthroughs for a few different parts of MeTA on the
[MeTA homepage][meta-website].
## Citing
If you used MeTA in your research, we would greatly appreciate a citation for
our ACL demo paper:
```latex
@InProceedings{meta-toolkit,
author = {Massung, Sean and Geigle, Chase and Zhai, Cheng{X}iang},
title = {{MeTA: A Unified Toolkit for Text Retrieval and Analysis}},
booktitle = {Proceedings of ACL-2016 System Demonstrations},
month = {August},
year = {2016},
address = {Berlin, Germany},
publisher = {Association for Computational Linguistics},
pages = {91--96},
url = {http://anthology.aclweb.org/P16-4016}
}
```
# Project setup
## Mac OS X Build Guide
Mac OS X 10.6 or higher is required. You may have success with 10.5, but
this is not tested.
You will need to have [homebrew][homebrew] installed, as well as the
Command Line Tools for Xcode (homebrew requires these as well, and it will
prompt for them during install, or you can install them with `xcode-select
--install` on recent versions of OS X).
Once you have homebrew installed, run the following commands to get the
dependencies for MeTA:
```bash
brew update
brew install cmake jemalloc lzlib icu4c
```
To get started, run the following commands:
```bash
# clone the project
git clone https://github.com/meta-toolkit/meta.git
cd meta/
# set up submodules
git submodule update --init --recursive
# set up a build directory
mkdir build
cd build
cp ../config.toml .
# configure and build the project
CXX=clang++ cmake ../ -DCMAKE_BUILD_TYPE=Release -DICU_ROOT=/usr/local/opt/icu4c
make
```
You can now test the system by running the following command:
```bash
./unit-test --reporter=spec
```
If everything passes, congratulations! MeTA seems to be working on your
system.
## Ubuntu Build Guide
The directions here depend greatly on your installed version of Ubuntu. To
check what version you are on, run the following command:
```bash
cat /etc/issue
```
Based on what you see, you should proceed with one of the following guides:
- [Ubuntu 12.04 LTS Build GuiExcerpt of 18,500 characters
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:0f8a1be18d520208, topic:nlp, topic:text-classification, readme:tokenization