NLP research started in 1930 and we have since made significant gains in the field, though a huge communication gap between humans and computers has yet to be bridged. This involves a lot of complex processing.
Understanding language means, among other things, identifying what a word or a phrase stands for and knowing how to properly link those concepts together in a logical way. Over time, the NLP-based systems may learn how to provide expert assistance to scientists, engineers, lawyers, and other professionals to complete a task in a fraction of a time that a human might require. It enables people and machines to interact more naturally with one another and can even expand human expertise. Its goal is to process the language we use and transform the text into structured data.
Natural language processing is one of the main abilities of a cognitive computing system. In this way, they can augment human expertise so that we can maximize the use of our time. Combined with automation, enterprises can leverage these systems to automate judgment-based activities involved in a business process. In this post, I share my experience of how NLP based solutions can be leveraged to increase the efficiency and quality of ticket management systems.Ĭognitive systems attempt to simulate functioning of human brain, imitating the way we learn from past experiences and use that knowledge for reasoning, making hypotheses, inferring, solving problems, or making decisions. Based on AI algorithms and driven by an increased need to manage unstructured enterprise information, NLP is influencing a rapid acceptance of more intelligent solutions in various business domains. Or, it may be employed to enhance customer experience by allowing users to post queries in their own language about products, services, or applications and receive immediate and accurate answers. It may be used to uncover relevant insight from a chain of email communication. Natural Language Processing (NLP) is one of the key components of cognitive automation that can be applied to a variety of industry segments to address their pain points. The evolution of cognitive automation is due to an emergence of various interdependent streams of Artificial Intelligence (AI). They are poised to improve productivity across multiple functions. These technologies bring along the potential for high-level automation. Cognitive computing, along with constituent technologies, seems to be yet another promising catalyst for enterprise transformation. Since the enterprise’s inception, technology has been paving the way for business innovation.