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Document AI combines text data, which has a time dimension, with other types of data, such as the position of an address in a business letter, which is spatial. Historically in machine learning spatial data was analyzed using a convolutional neural network , and temporal data using a recurrent neural network .
In machine learning, semantic analysis of a text corpus is the task of building structures that approximate concepts from a large set of documents. It generally does not involve prior semantic understanding of the documents. Semantic analysis strategies include: Metalanguages based on first-order logic, which can analyze the speech of humans.
The software-based document comparison process compares a reference document to a target document, and produces a third document which indicates (by colored highlighting or by differing font characteristics) information (text, graphics, formulas, etc.) that has either been added to or removed from the reference document to produce the target ...
Semantic similarity is a metric defined over a set of documents or terms, where the idea of distance between items is based on the likeness of their meaning or semantic content [citation needed] as opposed to lexicographical similarity. These are mathematical tools used to estimate the strength of the semantic relationship between units of ...
Layout analysis software, that divide scanned documents into zones suitable for OCR; Graphical interfaces to one or more OCR engines; Software development kits that are used to add OCR capabilities to other software (e.g. forms processing applications, document imaging management systems, e-discovery systems, records management solutions)
The following tables compare notable software frameworks, ... Vertex.AI, Intel: 2017 Apache 2.0: ... Comparison of numerical-analysis software;