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The Semantic Vectors package uses a Random Projection algorithm, a form of automatic semantic analysis. Other methods supported by the package include Latent Semantic Analysis (LSA) and Reflective Random Indexing. Latent Semantic Analysis (LSA) is a theory and method for extracting and representing the contextual-usage meaning of words by statistical computations applied to a large corpus of text. This library is used in semantic analysis and text mining.
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.
HyperGraphDB is a general purpose, open-source data storage mechanism based on a powerful knowledge management formalism known as directed hypergraphs. While a persistent memory model designed mostly for Knowledge management, Artificial Intelligence and Semantic web projects, it can also be used as an embedded object-oriented database for Java projects of all sizes. It could also be used as graph database or as (non-SQL) relational database.
ANTLR (ANother Tool for Language Recognition) is a powerful parser generator for reading, processing, executing, or translating structured text or binary files. It's widely used to build languages, tools, and frameworks. From a grammar, ANTLR generates a parser that can build and walk parse trees. Twitter search uses ANTLR for query parsing, with over 2 billion queries a day.
Semantic MediaWiki is an extension to the MediaWiki software (powering Wikipedia), which extends the Wiki with ideas from the Semantic Web. We focus on usability and tight integration. See the web site for further details.
SemanticScuttle is a social bookmarking tool experimenting with new features like structured tags and collaborative descriptions of tags. Originally a fork of Scuttle, it has overtaken its ancestor in stability, features and usability.
Framework for text mining, data integration and data analysis. Keywords: ontology and graph alignment, relation mining, warehouse, semantic database integration, bioinformatics, systems biology, microarray, Java.