Predictive query processing for complex system lifecycle management

Abstract

Techniques for identifying relevant, natural language documents within a data repository. An electronic document specifying natural language text describing an issue with a complex system is received. One or more portions are removed from the electronic document, where the portions are determined to satisfy one or more predefined filtering rules. A first set of terms are determined using a data dictionary structure, and a second set of terms are determined, where at least one term in the second set of terms satisfies at least one predefined pattern matching rule. A third set of terms are determined by processing the electronic document as an input to a machine learning model trained to recognize relevant terms within the electronic document. A synthesized electronic document is generated from the first, second and third sets of terms, and the synthesized electronic document is used to identify a set of relevant documents within the data repository.