Identification of key-value associations in documents using neural networks

Abstract

Aspects of the disclosure provide for mechanisms for identification of text fields in documents using neural networks. A method of the disclosure includes obtaining vectors, representative of objects in a document and processing the vectors to generate key hypotheses associating key(s) with one or more objects and value hypotheses associating value(s) with zero or more objects. The method further includes generating key-value association (KVA) hypotheses associating a selected key hypothesis with a selected value hypothesis and characterized by a KVA likelihood score that is based on at least a key likelihood score associated with the selected key hypothesis and a value likelihood score associated with the selected value hypothesis. The method further includes identifying one or more target KVAs of the document using the KVA likelihood scores of the generated KVA hypotheses.