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People sometimes want to know a specific reason for a page classification. For example, was the content category “Infectious Diseases” listed because the word “Cold” appeared on the page? 

The answer to the question lies in a thousand different numbers in a neural network. The numbers are tweaked as the model dissects innumerable pieces of training data, picking up on subtleties that may not be immediately obvious to humans. For example, a neural network can recognize:

  • Positive or negative words

  • Long or short sentences or paragraphs

  • FIrst, second, or third-person voice

  • Density of words of similar meaning

  • Certain words coinciding with certain images

The power of a neural network is manifest in its ability to recognize hidden patterns and correlations in raw data, cluster and classify the data, and continuously learn and improve over time.