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Multi-document summarization is an automatic procedure aimed at extraction of information from multiple texts written about the same topic. Resulting summary report allows individual users, such as professional information consumers, to quickly familiarize themselves with information contained in a large cluster of documents.
Angoss – Angoss Text Analytics provides entity and theme extraction, topic categorization, sentiment analysis and document summarization capabilities via the embedded; AUTINDEX – is a commercial text mining software package based on sophisticated linguistics by IAI (Institute for Applied Information Sciences), Saarbrücken.
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)
Document! X customizable HTML based templates, custom comment tags linked graphical object relationship diagrams internal links and links to .NET framework documentation types extracted and linked Doxygen: with XSLT caller and callee graphs, dependency graphs, inheritance diagrams, collaboration diagrams Epydoc: Haddock: Yes Yes HeaderDoc
The Document Understanding Conferences, [1] conducted annually by NIST, have developed sophisticated evaluation criteria for techniques accepting the multi-document summarization challenge. An ideal multi-document summarization system not only shortens the source texts, but also presents information organized around the key aspects to represent ...
The Document Foundation: OpenOffice.org Go-oo StarOffice: 2010-09 BSD: MPL-2.0: No cost: Linux: macOS: Solaris/Illumos: Unix: Windows: Microsoft 365: Microsoft: Forethought, Inc. [14] 2015 Android: rolling 2024 Proprietary: 89.95 - 679.95 2013 iOS: rolling 2024 1990 macOS: 2021 2021 2011 online: rolling 2024 1992 Windows: 2021 2021 NeoOffice ...
The cost to read a 1 KB item is 1 Request Unit (or 1 RU). Select by 'id' operations consume lower number of RUs compared to Delete, Update, and Insert operations for the same document. Large queries (e.g. aggregations like count) and stored procedure executions can consume hundreds to thousands of RUs depending on the complexity of the ...
Marek Jedliński, Tranglos Software MPL-2.0: Microsoft Windows Memonic: Nektoon AG Freemium [Notes 1] Android (not released yet), iOS, macOS, Microsoft Windows XP/Vista/7/Mobile web-based: Microsoft OneNote: Microsoft: Freemium [Notes 2] Android, macOS, iOS, Windows (desktop and mobile), PWA: MyInfo: Milenix Software Shareware: Windows MyNotex ...