Project Group: edu.ucla.sspace

S-Space Package

edu.ucla.sspace : sspace

The S-Space Package is a Natural Language Processing library for distributional semantics representations. Distributional semantics representations model the meaning of words, phrases, and sentences as high dimensional vectors or probability distributions. The library includes common algorithms such as Latent Semantic Analysis, Random Indexing, and Latent Dirichlet Allocation. The S-Space package also includes software libraries for matrices, vectors, graphs, and numerous clustering algorithms.

Last Version: 2.0.4

Release Date: Aug 11, 2013

graphical

edu.ucla.sspace : graphical_2.9.2

Last Version: 0.0.1

Release Date: Jul 27, 2012

Scala implementations for graphical models

edu.ucla.sspace : scalda

Scalda is a handful of simple implementations for graphical models such as Latent Dirichlet Allocation or the Dirichlet Process Mixutre Model

Last Version: 0.0.1

Release Date: Jun 3, 2012

S-Space Package

edu.ucla.sspace : sspace-wordsi

The S-Space Package is a collection of algorithms for building Semantic Spaces as well as a highly-scalable library for designing new distributional semantics algorithms. Distributional algorithms process text corpora and represent the semantic for words as high dimensional feature vectors. This package also includes matrices, vectors, and numerous clustering algorithms. These approaches are known by many names, such as word spaces, semantic spaces, or distributed semantics and rest upon the Distributional Hypothesis: words that appear in similar contexts have similar meanings.

Last Version: 2.0

Release Date: May 24, 2012