Semantic Vectors Package for creating and searching semantic vector indexes by wrapping Apache Lucene
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Semantic Vectors Description

Package for creating and searching semantic vector indexes by wrapping Apache Lucene The Semantic Vector indexes was created by applying a Random Projection algorithm to term-document matrices. The package was created as part of a project by the University of Pittsburgh Office of Technology Management, to explore the potential for automatically matching related concepts in the technology management domain, e.g., mapping new technologies to potentatially interested licensors. The Semantic Vectors project can be found at http://real.hsls.pitt.edu.The package creates a WordSpace model, of the kind developed by Stanford University's Infomap Project and other researchers during the 1990s and early 2000s. Such models are designed to represent words and documents in terms of underlying concepts, and as such can be used for many semantic (concept-aware) matching tasks such as automatic thesaurus generation, knowledge representation, and concept matching.The Semantic Vectors package uses a Random Projection algorithm, a form of automatic semantic analysis, similar to Latent Semantic Analysis (LSA) and its variants like Probabilistic Latent Semantic Analysis (PLSA). However, unlike other methods, Random Projection does not rely on the use of computationally intensive matrix decomposition algorithms like Singular Value Decomposition (SVD). This makes Random Projection a much more scalable technique in practice. Our application of Random Projection for Natural Language Processing (NLP) is descended from Pentti Kanerva's work on Sparse Distributed Memory, which in semantic analysis and text mining, this method has also been called Random Indexing. A growing number of researchers have applied Random Projection to NLP tasks, demonstrating: · Semantic performance comparable with other forms of Latent Semantic Analysis. · Significant computational performance advantages in creating and maintaining models. Requirements: · Java

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