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Saturday, April 14, 2018

In machine learning, semantic analysis of a corpus is the task of building structures that approximate concepts from a large set of documents. It generally does not involve prior semantic understanding of the documents.

Latent semantic analysis (sometimes latent semantic indexing), is a class of techniques where documents are represented as vectors in term space. A prominent example is PLSI.

Latent Dirichlet allocation involves attributing document terms to topics.

n-grams and hidden Markov models work by representing the term stream as a markov chain where each term is derived from the few terms before it.

See also




Text Analytics - Ep. 25 (Deep Learning SIMPLIFIED) - Unstructured textual data is ubiquitous, but standard Natural Language Processing (NLP) techniques are often insufficient tools to properly analyze this data. Deep learning has the potential...

  • Semantic analysis (knowledge representation)

Sentiment Analysis of Twitter Data Using... (PDF Download Available)
Sentiment Analysis of Twitter Data Using... (PDF Download Available). Source : www.researchgate.net

 
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