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Automatic summarization is the process of shortening a set of data computationally, to create a subset (a summary) that represents the most important or relevant information within the original content. Artificial intelligence algorithms are commonly developed and employed to achieve this, specialized for different types of data.
This table lists the machine-readable file formats that can be exported from reference managers. These are typically used to share data with other reference managers or with other people who use a reference manager. To exchange data from one program to another, the first program must be able to export to a format that the second program may import.
Text processing; tree numbering and sorting; custom tree icons; node checkboxes; checkbox filtering; search filtering; reminder alarms; compressed or encrypted notebooks; auto-minimize and/or auto-lock when idle; quick access key for fast notes; additional scratchpad; autosave of up to 9 previous file versions; automatic clipboard capturing ...
Data entry is the process of digitizing data by entering it into a computer system for organization and management purposes. It is a person-based process [ 1 ] and is "one of the important basic" [ 2 ] tasks needed when no machine-readable version of the information is readily available for planned computer-based analysis or processing.
Text Python Any 2013 1.0.1 (2021) Unlicense (PD) perldoc: Larry Wall: Text Perl Any 1994 5.16.3 Artistic, GPL phpDocumentor: Joshua Eichorn Text PHP Any 2000 3.0.0 LGPL for 1.x, MIT for 2+ pydoc: Ka-Ping Yee [1] Text Python Any 2000 in Python core Python: RDoc: Dave Thomas Text C, C++, Ruby Any 2001/12/14 in Ruby core Ruby: ROBODoc: Frans ...
Multi-document summarization is an automatic procedure aimed at extraction of information from multiple texts written about the same topic. The resulting summary report allows individual users, such as professional information consumers, to quickly familiarize themselves with information contained in a large cluster of documents.
KNIME workflows can be used as data sets to create report templates that can be exported to document formats such as doc, ppt, xls, pdf and others. Other capabilities of KNIME are: KNIMEs core-architecture allows processing of large data volumes that are only limited by the available hard disk space (not limited to the available RAM). E.g.
As of version 1.6 (2010), it supports text entries and hyperlinks to the World Wide Web, but not graphic image linking or embedding. Development of the original Tomboy software ceased in 2017. Starting in 2017 the development team rewrote the software from scratch, for ease of maintenance and installation, renaming it tomboy-ng . [ 4 ]
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