Semantic Analysis

I want to go through the Wikipedia series on Machine Learning and Data mining. Data mining is the process of extracting and discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems.

Date Created:
0 86

References


Notes

In machine learning, semantic analysis of a text 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

Semantic analysis strategies include:

  • Metalanguages based on first-order logic, which can analyze the speech of humans
  • Understanding the semantics of a text is symbolic grounding: if language is grounded, it is equal to recognizing a machine-readable meaning. For the restricted domain of spatial analysis, a computer-based language understanding system was demonstrated.
  • Latent Semantic Analysis (LSA), a class of techniques where documents are represented as vectors in a term space. A prominent example is probabilistic latent semantic analysis (PLSA)
  • Latent Dirichlet allocation, which involves attributing document terms to topics
  • n-grams and hidden Markov models, which work by representing the term stream as a Markov chain, in which each term is derived from preceding terms

Comments

You can read more about how comments are sorted in this blog post.

User Comments