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Full-Text Articles in Physical Sciences and Mathematics
Natural Language Document And Event Association Using Stochastic Petri Net Modeling, Michael Thomas Mills
Natural Language Document And Event Association Using Stochastic Petri Net Modeling, Michael Thomas Mills
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The purpose of this research is to design and implement a new methodology that captures the natural language understanding of events from English natural language text and model it using Stochastic Petri Nets. To establish a baseline of recent natural language processing (NLP) and understanding (NLU) research, two surveys are presented. One is a general survey in NLP and NLU methodologies for processing multi-documents. It summarizes and presents methodologies in terms of their features, capabilities, and maturity. The second survey focuses on graph-based methods for NL text processing and understanding and analyzes them in terms of their functional descriptions, capabilities …
A Latent Dirichlet Allocation/N-Gram Composite Language Model, Raymond Daniel Kulhanek
A Latent Dirichlet Allocation/N-Gram Composite Language Model, Raymond Daniel Kulhanek
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I present a composite language model in which an n-gram language model is integrated with the Latent Dirichlet Allocation topic clustering model. I also describe a parallel architecture that allows this model to be trained over large corpora and present experimental results that show how the composite model compares to a standard n-gram model over corpora of varying size.