edu.ucla.sspace maven依赖

edu.ucla.sspace/sspace-wordsi 共有1个版本,总共被引用了2次

被引用次数最多的版本是2.0 ,其被引用次数为2 。

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.

edu.ucla.sspace/graphical_2.9.2 共有1个版本,总共被引用了0次

被引用次数最多的版本是0.0.1 ,其被引用次数为0 。

graphical

edu.ucla.sspace/scalda 共有1个版本,总共被引用了0次

被引用次数最多的版本是0.0.1 ,其被引用次数为0 。

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

edu.ucla.sspace/sspace 共有6个版本,总共被引用了0次

被引用次数最多的版本是2.0.4 ,其被引用次数为0 。

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.
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