Abstract: A computer implemented method for managing tokens on a blockchain platform. The method uses a number of processor units to receive a first set of attributes associated with a number of items and a second set of attributes associated with a number of offers to purchase the number of items. The number of processor units creates an item token on the blockchain platform for each item from the number of items based on the first set of attributes to form a number of item tokens. The number of processor units create a request token on the blockchain platform for each offer to purchase based on the second set of attributes to form a number of request tokens. The number of processor units create a number of matching tokens and a number of trades based on the matching tokens.

Abstract: A method, apparatus, system, and computer program code for intelligent data discovery with dynamic ontology are provided. According to one illustrative embodiment, the method using a number of processors to perform the steps of: identifying a set of data items in unstructured content using a dynamic data schema populated from a dynamic ontology; and responsive to identifying a data item that is not recognized in the data schema: storing the data item with labels; generating a weight for the data item; and responsive to the weight exceeding a threshold, updating the schema to include the data item that was not recognized.

Abstract: A method, apparatus, system, and computer program code for dynamically modeling multi-tenant data in a machine learning platform. A recommendation engine receives a first data set from a user. The recommendation engine characterizes the first data set to determine data attributes and data characteristics of the first data set. The recommendation engine aligns the data attributes of the first data set with a second data set according to an ontology. Based on the data characteristics of the first data set, the recommendation engine identifies a set of pre-trained models that was trained from training parameters selected from data attributes and data characteristics of a second data set. The recommendation engine recommends the set of pre-trained models to the user.

Abstract: A method, apparatus, system, and computer program code for intelligent data discovery with dynamic ontology are provided. According to one illustrative embodiment, the method using a number of processors to perform the steps of: identifying a set of data items in unstructured content using a dynamic data schema populated from a dynamic ontology; and responsive to identifying a data item that is not recognized in the data schema: storing the data item with labels; generating a weight for the data item; and responsive to the weight exceeding a threshold, updating the schema to include the data item that was not recognized.