As human beings we express everything either verbally or through written form, which carries lot of information. But how do we use all this information and derive benefits out of it?
Computers are and have always been great at working with spreadsheet data and database tables which are typically structured data. But as we human beings generate data through speech or text, the focus shifts in dealing with completely unstructured data.
Unstructured data does not fit into the typical row and column structure as promoted by the relational databases and major share of data generated is unstructured. So how can we get computers to process unstructured data and get business value out of it?
In comes Natural Language Processing, or NLP, the sub-field of AI that helps in enabling computers to understand and process human languages.
Nowadays it’s not about understanding the data just from certain keywords present in the data, which is the old fashioned way, but more of understanding the meaning behind those words. This way it is possible to detect irony or even perform sentiment analysis.
A biopharmaceutical company wanted to mine clinical trials with the objective of acquiring high value information. Though clinical trial reports offered valuable information from structured and searchable information, there was information waiting to be tapped from unstructured text. NLP stood the biopharmaceutical company in good stead in helping clinical decision makers acquire information that otherwise would have eluded the company.
How is NLP used in such scenarios?
Using NLP means turning attention on ‘words’ and how words come together to form a sentence. And most importantly, it is a requisite to know what those words actually convey.
Getting value out of NLP is then to leverage syntax as well as semantic analysis wherein techniques like parsing, sentence breaking, segmentation and stemming are put to use along with the algorithms used for unearthing the meaning of words as well as understand sentence structure.
Where can NLP be applied?
Let’s look at some of the cases where Natural Language Processing has been put to good use.
Take the case of a company that wants to reap value from social landscape in terms of understanding customer sentiments and customer intent detection. Natural language processing serves the company by way of:
Sentiment Analysis
NLP can be used to understand how customers feel about a product or a service offered through the comments, tweets, or feedbacks they provide on sources like social media. Knowing what customers like and dislike can benefit an organization in multiple ways.
Text Classification
This technique helps in organizing information according to need, for example classifying whether an email is spam or not-spam.
Natural language processing is also used widely across operations, as in the case of a brand that wants to know how ads are performing and how to serve the right ads for right customers. NLP is also being used in healthcare in the way it helps optimize care delivery.
Ad Optimization
NLP helps in identifying customers who are interested in a product or service, which helps companies to handle their ad budget more efficiently by targeting only a segment of customers.
Care Optimization
NLP is used in improving care delivery, disease diagnosis and bringing costs down. The fact that clinical documentation can be utilized in healthcare is well demonstrated wherein patients can be better understood and benefited through better healthcare.
When a leading provider of Innovative Business Solutions wanted to leverage user comments, description and reviews to strengthen product categorization, Saksoft helped the client use word embedding and Recurrent Neural Networks (RNN) with Tensorflow backend to make the most of NLP, enhance predictive accuracy and achieve its objective.
