Natural Language Processing and its applications in e-business

Abstract

The advent of big data and the ability to extract insights from unstructured data has opened new avenues for companies. In this scientific article we have gathered different examples of application of Natural Language Processing (NLP) specifically in the electronic business environment. The main objective was to investigate what kind of analyzes and techniques are being used to extract knowledge from Big data, more concretly unstructured data, and within this type, textual data and what concrete applications derive from NLP in the context of e-business. Being NLP a type of Artificial Intelligence (AI) that uses Machine Learning (ML) and Deep Learning (DL) with the objective of developing a technology that learns, and takes decisions based on what it learned, it was important to understand what a ML workflow is like and therefore, the literatuere revision is very focused on this point. It was concluded that NLP is a complex process whose applications are diverse and relevant in the context of Electronic Business. Today, NLP is used to complete tasks such as text classification, content filtering, sentiment analysis, language modeling, translation, and summarization and applications such as chatbots, voice assistants and recommendation systems. In the future, it is expected that the NLP will have greater influence in different business areas such as the management of new products and recommendation systems; segmentation, segmentation and analysis of customers and users; brand positioning, communication and marketing; competitor analysis; and risk management, sustainability and social responsibility. Specialists in the area also believe that there will possibly be a paradigm shift in AI that will use Reinforcement Learning techniques, which will allow the development of more advanced, adaptive and multipurpose AI agents. It is also to be expected that humans and machines cohabit in a more collaborative way.