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A word processor (WP) [1] [2] is a device or computer program that provides for input, editing, formatting, and output of text, often with some additional features.. Early word processors were stand-alone devices dedicated to the function, but current word processors are word processor programs running on general purpose computers.
Microsoft Excel is a spreadsheet editor developed by Microsoft for Windows, macOS, Android, iOS and iPadOS.It features calculation or computation capabilities, graphing tools, pivot tables, and a macro programming language called Visual Basic for Applications (VBA).
As an example, VBA code written in Microsoft Access can establish references to the Excel, Word and Outlook libraries; this allows creating an application that – for instance – runs a query in Access, exports the results to Excel and analyzes them, and then formats the output as tables in a Word document or sends them as an Outlook email.
The array, set and dictionary binary types are made up of pointers - the objref and keyref entries - that index into an object table in the file. This means that binary plists can capture the fact that - for example - a separate array and dictionary serialized into a file both have the same data element stored in them.
Machine-readable dictionary (MRD) is a dictionary stored as machine-readable data instead of being printed on paper. It is an electronic dictionary and lexical database. A machine-readable dictionary is a dictionary in an electronic form that can be loaded in a database and can be queried via application software.
A dictionary writing system (DWS), or dictionary production/publishing system (DPS) is software for writing and producing a dictionary, glossary, vocabulary, or thesaurus. It may include an editor, a database , a web interface for collaborative work, and various management tools.
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In applied mathematics, k-SVD is a dictionary learning algorithm for creating a dictionary for sparse representations, via a singular value decomposition approach. k-SVD is a generalization of the k-means clustering method, and it works by iteratively alternating between sparse coding the input data based on the current dictionary, and updating the atoms in the dictionary to better fit the data.