Machine Learning Helps Humans Perform Text Analysis

To augment that approach, we've found that we can use machine learning to improve the semantic data models as the data set evolves. Our specific use-case is text data in millions of documents. We've found that machine learning facilitates the storage and exploration of data that would otherwise be too vast to support valuable insights. Machine Learning (ML) allows for a model to improve over time given new training data, without requiring more human effort. For example, a common text-classification benchmark task is to train a model on messages for multiple discussion board threads and then later use it to predict what the topic of discussion was (space, computers, religion, etc).