How Does Natural Language Processing Work?
Recently, researchers have begun to use natural language processing to understand the meaning of large sets of documents from an analysis perspective. This means that they can understand the different contexts and nuances that phrases mean. After all, when someone is told not to "have a cow," it doesn't mean what the words literally mean, but it takes NLP to understand that.
What Is Data Mining?
Data mining is the process of analyzing data. It looks for patterns to turn that data into information and better decisions. Data mining is algorithm-based and finds patterns in large collections of data. This process is essential in cognitive technology because when algorithms develop and self-teach, they tend to find things that humans don't know to look for. Data mining is also important because it presents a potentially more efficient and thorough way of interpreting data.
What Is Pattern Recognition?
Pattern recognition is a branch of machine learning focused on categorizing information or finding anomalies within data. For example, facial pattern recognition might be used to determine the age and gender of a person in a photo. Pattern recognition tends to be based on probability, so there is a chance that it does not accurately categorize information. Pattern recognition is also typically controlled by an algorithm. This means that the computer will continue to make guesses until it finds a pattern that makes sense and matches with what we know is true or until the probability of any other pattern remaining is too small to be considered.
When data mining, pattern recognition, and natural language processing come together to mimic cognitive technology functions, the result is significant opportunities for advancement in technology. Newly developed algorithms can give computers the ability to learn and create at unprecedented levels, leading to artificially intelligent machines that mimic human thought patterns.