Microsoft Technology Licensing, LLC

Ivan Vujic

Aljosa Obuljen

Sanjay Krupakar Bhat

Karim Taji Farouki

Milos Lazarevic

Katrika Marie Morris

Milan Sesum

Catherine William Neylan

Jennifer Michelstein Halberstam

Naresh Jain

Tumu Sree Bharath

Milos Jovanovic

Dusan Lukic

Jeet Mukeshkumar Patel

Andreja Ilic

Abhas Sinha

Marko Rakita

Gopalakrishnan Venkateswaran

Ajit Kumar Singh

Dhiresh Kumar Nagwani

Aleksandar Sretenovic

Tamara Paunovic

Sasa Vuckovic

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.

Converting an image into a structured table

A dynamic presentation of contextually relevant content during an authoring experience. As a user writes about a topic, the authored content is analyzed to identify one or more keywords that may be used to identify, retrieve and present suggested content to the user. The suggested content may be received from one or more resources, such as a search engine, a data store associated with the user, social media resources or other local or remote files. Techniques described herein might also select the keywords from authored content based on a cursor position. As a result, the suggested content may change as the cursor moves to a new position in the authored content. In addition, techniques described herein provide a user interface control that allows for the selection and de-selection of one or more keywords, which allows a user to tailor the suggested content by toggling one or more controls.

Dynamic presentation of suggested content

One or more components of an image document may be detected and extracted in order to create a flow document from the image document. Components of an image document may include text, one or more paths, and one or more images. The text may be detected using optical character recognition (OCR) and the image document may be binarized. The detected text may be extracted from the binarized image document to enable detection of the paths, which may then be extracted from the binarized image document to enable detection of the images. In some examples, the images, similar to the text and paths, may be extracted from the binarized image document. The extracted text, paths, and/or images may be stored in a data store, and may be retrieved in order to create a flow document that may provide better adaption to a variety of reading experiences and provide editable documents.

Detecting and extracting image document components to create flow document

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Belgrade, Republic of Serbia

Ivan Vujic