Natural Language Processing (NLP) is fast becoming essential to many new business functions, from chatbots and digital assistants like Alexa, Siri, and Google Home, to compliance monitoring, BI, and analytics. NLP tools and techniques help businesses process, analyze, and understand all of this data in order to operate effectively and proactively. Now, even Google Analytics offers support for NLP, which is revolutionary in its own way.
The input to natural language processing is a simple stream of Unicode characters, and basic processing is required to convert this character stream into words, phrases, and syntactic markers which can then be used to better understand the content. Basic processing includes language identification, sentence detection, lemmatization, decompounding, structure extraction, tokenization, entity and phrase extraction.
Acquiring content from multiple sources and then extracting information from that content will likely involve many steps and a large number of computational stages. This is why it’s vital to provide traceability for all outputs. One can then trace back through the system to identify exactly how that information came to be, supporting quality analysis and validation purposes.
Content understanding can never be complete without some human intervention. One needs humans to discover new patterns and for creating, cleansing or choosing lists of known entities, to name a few.
For example, you may want to leverage crowd-sourcing to scale out human-aided processes and also find ways to incorporate human review as part of your standard business process (i.e. form fills etc.).
NLP might be new – but it taking the world by storm. Just like mTrakr and majority other fintech companies, NLP is just getting started. As human lives progress and the quest for efficiency continues – it might not be wrong to say that few things that have gone digital like expense management or language processing, are the ones that will survive.