Machine learning derives meaning from big data for customer care

In my last post, I discussed how human agents and human assisted virtual agents (HAVAs) can work together when machine learning and artificial intelligence are applied to customer care systems. Now let's take it a step further. In machine learning you often need to compare or "match" things. For example, when you are looking for the right answer in a database, you compare the question to the possible answers stored there. If you want to sort intents into buckets (so-called clustering) you need to compare them with each other and see how similar they are.