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The space of documents is then scanned using HDBSCAN, [20] and clusters of similar documents are found. Next, the centroid of documents identified in a cluster is considered to be that cluster's topic vector. Finally, top2vec searches the semantic space for word embeddings located near to the topic vector to ascertain the 'meaning' of the topic ...
It was developed for, and is used extensively by, the Python project for documentation. [9] Since its introduction in 2008, Sphinx has been adopted by many other important Python projects, including Bazaar, SQLAlchemy, MayaVi, SageMath, SciPy, Django and Pylons. It is also used for the Blender user manual [10] and Python API documentation. [11]
LibreLogo is an integrated development environment (IDE) for computer programming in the programming language Python, which works like the language Logo using interactive vector turtle graphics. Its final output is a vector graphics rendition within the LibreOffice suite. It can be used for education and desktop publishing.
GF was first created in 1998 at Xerox Research Centre Europe, Grenoble, in the project Multilingual Document Authoring. At Xerox, it was used for prototypes including a restaurant phrase book, a database query system, a formalization of an alarm system instructions with translations to 5 languages, and an authoring system for medical drug ...
Jupyter Notebook (formerly IPython Notebook) is a web-based interactive computational environment for creating notebook documents. Jupyter Notebook is built using several open-source libraries, including IPython, ZeroMQ, Tornado, jQuery, Bootstrap, and MathJax. A Jupyter Notebook application is a browser-based REPL containing an ordered list of ...
Office Open XML (also informally known as OOXML) [5] is a zipped, XML-based file format developed by Microsoft for representing spreadsheets, charts, presentations and word processing documents. Ecma International standardized the initial version as ECMA-376.
In natural language processing, a word embedding is a representation of a word. The embedding is used in text analysis.Typically, the representation is a real-valued vector that encodes the meaning of the word in such a way that the words that are closer in the vector space are expected to be similar in meaning. [1]
There are two basic types of outliners: one-pane or intrinsic, and two-pane or extrinsic, each with its strengths and weaknesses.. A one-pane outliner is known as an intrinsic outliner because the text itself is organized into an outline format—individual sections (such as paragraphs) of text can be collapsed or expanded, while keeping others in view.