Knowledge Base

Overview

A knowledge base is a repository of structured knowledge, often organized using semantic relationships, that is designed to be readily accessed and used by artificial intelligence (AI) systems. A knowledge base can include facts, concepts, rules, and other types of information that help an AI system perform tasks, answer questions, and make decisions based on a broad understanding of the world. The information is structured and organized to be easily accessed and reasoned with by AI models.

How AI Knowledge Bases Work

• Storing and Organizing Information: AI knowledge bases can store vast amounts of information from various sources, including documents, emails, websites, and databases. For instance, a medical knowledge base might store patient records, drug interactions, and disease information.
• Understanding User Queries: These knowledge bases use natural language processing (NLP) to understand the intent behind user questions, allowing for more effective responses. For example, a user query such as "what are the side effects of drug X?" will be interpreted to find a specific, relevant answer.
• Learning from User Interactions: AI knowledge bases learn from user interactions and data input to improve their accuracy and relevance over time. For example, if a user often selects a particular answer or rating as correct, the model will learn to prioritize that answer more in future.
• Providing Relevant Information: These systems can provide relevant information to users without direct human intervention, acting as an efficient data source. This is common in recommendation systems, or question answering systems.
• Automatically Generating Answers: AI knowledge bases can automatically generate answers from structured company documents, rather than just providing simple facts or links.

AI Decision Support

It helps AI models in decision-making and question answering tasks, acting as a resource for the model to use.

Related Concepts

• Knowledge Graph
• Retrieval
• RAG