Abstract: A system for converting an image of an unstructured table into a structured table is provided. The system may comprise a memory storing machine readable instructions. The system may include a processor to receive an image of a unstructured table and convert the image of the unstructured table into a structured table. Converting the image of the unstructured table into the structured table may include providing cell mapping and low confidence determination to highlight potentially misconverted content. The low confidence determination may be based on a first input and a second input. The processor may export the structured table, upon validation, to an application that supports structured tables.

Abstract: A system for converting an image of an unstructured table into a structured table is provided. The system may comprise a memory storing machine readable instructions. The system may include a processor to receive an image of a unstructured table and convert the image of the unstructured table into a structured table. Converting the image of the unstructured table into the structured table may include providing cell mapping and low confidence determination to highlight potentially misconverted content. The low confidence determination may be based on a first input and a second input. The processor may export the structured table, upon validation, to an application that supports structured tables.

Abstract: Technologies are described to detect captions in an unstructured or semi-structured document. Text regions may be defined by grouping letters based on proximity. Text regions that are not in close proximity of a graphical element may be filtered out. Candidate captions may be generated based on format, style, indentation, and/or location of text near graphical elements. Sequences of graphical elements and candidate captions may be ordered and a final combination of graphical elements and captions defining connections between captions and respective graphical element may be determined based on an analysis of relative positions and style relationships.

Abstract: Detection of a document type of a document is provided. An application such as a document processing application analyzes a document to detect features of the document and pages of the document, based on an action selecting the document. The features include declarative and separative features. A type of the pages is detected based on the features. The type of the pages and values of the features of the document are aggregated to identify the document type of the document.

Abstract: Detection of a sidebar in a document is provided. An application such as a document processing application processes a page of the document to detect the sidebar. Components of the page are analyzed to detect borders. The one or more borders are processed to discard a subset of the one or more borders identified as false positive candidates. In response to detecting the borders, the borders are processed to detect the sidebar that includes the borders. In response to a failure to detect the borders, the components are processed to detect the sidebar that lacks the borders.

Abstract: Detection of a document type of a document is provided. An application such as a document processing application analyzes a document to detect features of the document and pages of the document, based on an action selecting the document. The features include declarative and separative features. A type of the pages is detected based on the features. The type of the pages and values of the features of the document are aggregated to identify the document type of the document.

Abstract: Technologies are described herein for inferring the layout intent associated with explicitly formatted document elements in a document. The layout type of a document having explicitly formatted document elements is determined. Once the layout type for the document has been determined, the layout intent of explicitly formatted document elements in the document may be determined based, at least in part, on the determined layout type of the document. Heuristic algorithms and/or machine learning classifiers may determine the layout intent of the explicitly formatted document elements in the document. An intent-based document is then created using the inferred layout intent for some or all of the explicitly formatted document elements in the document. The intent-based document may then be provided to an intent-based rendering or authoring application for rendering based upon the inferred layout intent.