Natural Language Processing (NLP) is a technology that has been around since
the 1970s in some form or another. It is in a sense a subset of artificial
intelligence in computer programming. NLP is a relatively new field, but one
that is quickly expanding and creating enormous implications for the human
experience with computing, big data analytics, and machine learning.
In this article we will define NLP and explore its various applications in
text analytics, big data analytics, and machine learning systems to build an
understanding of how it can be used to improve the human experience with
computing by making computers better understand human languages.
Introduction: What are Natural Language Processing Techniques?
Section keywords: natural language processing techniques, features of
natural language processing techniques, types of natural language processing
techniques
The Importance of Machine Learning in NLP Programming
Machine Learning has been used to improve text analysis software. It is the
process of building a machine’s capability to learn and adapt when exposed to
new data.
One way to find out whether machine learning has been used in a software is
by looking at the back-end. If you see that there is a lot of text analysis
logic, then it means that there is some AI involved in the programming. Text
analysis programs can do much more than just identifying sentiment or matching
words with synonyms. They can also be used for:
1) Detecting plagiarism and duplicate content
2) Identifying and classifying key words and phrases
3) Understanding user intent
4) Understanding customer needs
The Role of NLP Programming in Marketing and How to Leverage It Effectively
NLP is one of the most effective and powerful tools to leverage for your
marketing and sales team.
It can help you understand your customer’s behavior and how they react to
different marketing channels and messages.
The best part about NLP is that it helps you communicate with them in a more
personalised way which can improve their conversion rates.
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