Big Data’s Role in Natural Language Processing


Jeff Bertolucci of Information Week reports, "Computers do many things faster and more efficiently than the human brain, but they're decidedly inferior when it comes to extracting meaning from human language. As founder Mark van Rijmenam writes in a recent blog post, the key stumbling block here is that computers understand 'unambiguous and highly structured' programming language, while human language is a minefield of nuance, emotion, and implied intent. Van Rijmenam also quotes a Chronicle of Higher Education post by Geoffrey Pullum, a professor of general linguistics at the University of Edinburgh. Pullum outlines three prerequisites for computers to master human language: 'First, enough syntax to uniquely identify the sentence; second, enough semantics to extract its literal meaning; and third, enough pragmatics to infer the intent behind the utterance, and thus discerning what should be done or assumed given that it was uttered.' "


Bertolucci goes on, "Pragmatics pose the biggest challenge in this field, van Rijmenam writes. 'Often a lot more is told by what is not said in a sentence or conversation than what is said.' There's no shortage of technology firms working on natural language processing solutions that teach computers better human language skills. For example, the London startup The Outside View is developing a voice analytics tool that studies the mood and quality of sales calls to determine the likelihood of a sale closing. Rob Symes, CEO of The Outside View, and Jason Filos, head of its voice analytics effort, told us how predictive analytics can help sales teams unleash the potential of their voice recordings, CRM data, and email."


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Image: Courtesy Flickr/ sjcockell