ESA for Text Analysis

Learn how Explicit Semantic Analysis (ESA) can be used for machine learning operations on text.

Explicit knowledge often exists in text form. Multiple knowledge bases are available as collections of text documents. These knowledge bases can be generic, for example, Wikipedia, or domain-specific. Data preparation transforms the text into vectors that capture attribute-concept associations. ESA is able to quantify semantic relatedness of documents even if they do not have any words in common. The function FEATURE_COMPARE can be used to compute semantic relatedness.