Chatbots and virtual assistants are among the leading portals for accessing knowledge as consumers, employees, patients, and more. Machine learning and an intuitive interface that permits natural language questions can help make chatbots very useful. However, it is vital to have an information strategy involving taxonomies and ontologies to make Artificial Intelligence (AI)-powered chatbots function at top performance.
There is a natural relationship between AI, chatbots, and taxonomies. Taxonomies are the foundational level of data organization because when information is structured and indexed as in a taxonomy, users and AI technology powered chatbots can find what they need by working down to more specific categories, up to a more inclusive topic, or sideways to related topics. In other words, what is useful for the users is also suitable for chatbots.
Furthermore, taxonomies, and their more complex relatives, ontologies, interact with, support, and drive AI technologies in many ways. For instance, the automation and benefits that organizations realize from AI-powered chatbot applications are only as good or bad as the quality of the data used. The better the information is organized, the better the data quality, the better it is aligned to the business and end-user goals. Consequently, it is easier for the AI to utilize the information. Incomplete, erroneous, or biased data will adversely affect both the user experience and your brand.
Therefore, for a well-functioning system that delivers the most relevant information to people, consider the relationship between taxonomies, chatbots, and AI.
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