Natural Language Processing
Natural Language Processing in Use
You may have seen a language to language translation that took things a bit too literally. Written communication is often open to interpretation largely because of metaphors, context, and homographs (identically spelled words with different meanings). Consider these examples: Are you close enough to close the door? I cannot bear to see the bear treated badly. She is buried in a sea of paperwork. I hate that I didn’t go to the restaurant sooner. Literal translations would be next to impossible.
That is where Natural Language Processing comes in. NLP combines AI and deep learning with linguistics to “understand” text, taking contextual nuances into account.
Explore a few common use cases for Natural Language Processing:
With AI-Driven Data Capture Automation, text is captured in context, much the way a human would read a document. This enables NLP Logix to process non-standard, messy, or overprinted documents. Data can then be extracted and properly routed. Humans would potentially only need to handle the exceptions. Learn more about Data Capture Automation here.
Search engines use NLP to present relevant results based on learned search behaviors.
If you get even close to the spelling of a word, the search engine can interpret what you meant to type. If you key in three digits, the search engine is likely to assume you are looking for the location of an area code, a flight number will provide flight status, and a ticker symbol will return stock price results.
Your email server uses NLP for email filtering when your account sorts your emails by Promotional, Social, or Spam.
Your corporate emails (or other incoming documents) can be sorted by priority, department, or topic when NLP is used to interpret the contents.
Sentiment Analysis can be used to determine if data is positive, negative, or neutral.
This Natural Language Processing technique is especially helpful for businesses processing large quantities of customer feedback via surveys, reviews, online comments/articles, or other sources.
Chatbots that incorporate Natural Language Processing are capable of understanding text and answering appropriately.
Thanks to Machine Learning, they can also learn over time to progressively improve their responses.
Available 24/7, they are best used for routine questions, routing difficult queries to the human agents.
Incorporate NLP into Your Processes
The use of NLP tools to interpret, analyze, and understand your data is typically one step in your overall automation workflow.
NLP Logix provides the understanding on how the pieces fit together to achieve the most valuable insights from your data. With 4 patents in the areas of Data Extraction, Computer Vision, and the ability to interpret data, NLP Logix is a leader in Data Capture Automation.
