Natural Language Generation (NLG)
Natural Language Generation (NLG) is a subfield of Artificial Intelligence and Computational Linguistics that focuses on the creation of written or spoken narrative from a dataset. It involves the application of algorithms and computational methodologies to generate coherent, contextually relevant text that mirrors human language patterns.
The process encompasses several stages, including content planning, sentence planning, and text realization, to transform structured data into intelligible narratives. NLG systems are designed to interpret and find patterns in data, and then articulate those findings in a natural, understandable way, bridging the gap between machine understanding and human communication.
NLG has a wide array of applications across various domains in AI and ML. In the business intelligence sector, NLG tools can automatically generate comprehensive reports from sales or financial data, highlighting key trends, anomalies, and insights without manual intervention. For instance, an NLG system can take sales figures spread across different regions and time periods, and produce an analytical report that summarizes the overall performance, points out regions with exceptional sales, and identifies periods of growth or decline.
In customer service, NLG can power chatbots and virtual assistants, enabling them to produce human-like responses based on user queries and data. For example, a chatbot for a banking service might use NLG to inform a customer about their spending habits, account balances, or investment opportunities based on their transaction history and account data.
In the media and news industry, NLG technologies are used to automatically generate news articles for topics like sports events and financial market summaries. These systems can analyze game statistics or market data in real-time and produce articles that summarize the event's outcomes, player performances, or market trends, often indistinguishable from those written by human journalists.
NLG is also increasingly used in personalized content creation, such as generating product descriptions for e-commerce websites, personalized emails or messages based on user behavior and preferences, and even creative storytelling or poetry, showcasing the versatility and potential of natural language generation in enhancing human-machine interaction.