International Business Machines Corporation

Jeremy John Salsman

Andrew Ronald Freed

Paul Richard Chmielewski

John Martin Ludden

Elizabeth T Dettman

Troy Biesterfeld

Improved data ingestion techniques are provided. A data set comprising records is received, where each record contains one or more fields. A group of fields is identified, where each of the fields has a common metadata attribute. Metrics are determined for the group based on metadata associated with each field, and weight values are assigned to each of the metrics. A natural language processing (NLP) measure and a discreteness measure are generated for the group of fields based on the metrics and the weight values. A processing workflow is selected to use when ingesting data from the group of fields into a corpus, based on comparing the NLP measure and the discreteness measure to one or more predefined thresholds, and each of the fields in the group of fields are processed using the processing workflow.

Inferring confidence and need for natural language processing of input data

A method, apparatus and computer program product are provided for implementing a level bias function for branch prediction control for generating test simulation vectors. User selected options are received for a set of constraints for generating test simulation vectors for branch conditional instructions. Current resource values for predicting a branch for a branch conditional instruction are read. A branch operand field is generated to include a set of valid values using the current resource values and based upon said user selected constraints. The branch operand field defines conditions under which a branch is taken.

Method, apparatus and computer program product for implementing level bias function for branch prediction control for generating test simulation vectors

Growing community of inventors

Rochester, MN, United States of America

Jeremy John Salsman