Abstract: A system captures and utilizes expert knowledge in artificial intelligence. The system includes a knowledge capture module for extracting expert knowledge from subject matter experts in a conversational format and a knowledge management module for cataloging and summarizing the extracted knowledge. The system also includes a digital subject matter expert (dSME) module for ingesting the cataloged knowledge and using it to guide users in building AI models. A chatbot interacts with a user and selects the appropriate dSME module that is relevant to the user request. The system attempts to answer the user request based on the dSME module. If the dSME module lacks knowledge to solve the problem, the system uses a set of tools, for example, internet based search engine to solve the problem.

Abstract: A system makes predictions using a machine learning model combined with a knowledge model. The system provides input data to a knowledge model and a machine learning based model. The machine learning based model is trained to make predictions based on input data. The system provides the outputs of the machine learning based model and the knowledge model to an ensemble model configured to combine results of the knowledge model and the machine learning based model. The system can be used for several applications. For example, the system may classify an input text based on a hierarchy of categories. The system may perform fault detection in time series data by identifying an anomaly data point and predicting whether the anomaly data point is a fault.

Abstract: A system makes predictions using a machine learning model combined with a knowledge model. The system provides input data to a knowledge model and a machine learning based model. The machine learning based model is trained to make predictions based on input data. The system provides the outputs of the machine learning based model and the knowledge model to an ensemble model configured to combine results of the knowledge model and the machine learning based model. The system can be used for several applications. For example, the system may classify an input text based on a hierarchy of categories. The system may perform fault detection in time series data by identifying an anomaly data point and predicting whether the anomaly data point is a fault.

Abstract: A system makes predictions using a machine learning model combined with a knowledge model. The system provides input data to a knowledge model and a machine learning based model. The machine learning based model is trained to make predictions based on input data. The system provides the outputs of the machine learning based model and the knowledge model to an ensemble model configured to combine results of the knowledge model and the machine learning based model. The system can be used for several applications. For example, the system may classify an input text based on a hierarchy of categories. The system may perform fault detection in time series data by identifying an anomaly data point and predicting whether the anomaly data point is a fault.