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English: A PDF version of the en:Python Programming Wikibook. This file was created with MediaWiki to LaTeX . The LaTeX source code is attached to the PDF file (see imprint).
Learning Object Metadata is a data model, usually encoded in XML, used to describe a learning object and similar digital resources used to support learning. The purpose of learning object metadata is to support the reusability of learning objects, to aid discoverability , and to facilitate their interoperability, usually in the context of ...
Meta-learning [1] [2] is a subfield of machine learning where automatic learning algorithms are applied to metadata about machine learning experiments. As of 2017, the term had not found a standard interpretation, however the main goal is to use such metadata to understand how automatic learning can become flexible in solving learning problems, hence to improve the performance of existing ...
Metadata This file contains additional information, probably added from the digital camera or scanner used to create or digitize it. If the file has been modified from its original state, some details may not fully reflect the modified file.
One of the key issues in using learning objects is their identification by search engines or content management systems. [13] This is usually facilitated by assigning descriptive learning object metadata. Just as a book in a library has a record in the card catalog, learning objects must also be tagged with metadata. The most important pieces ...
First of all, a concept is a simple version of a Unified Modeling Language (UML) class. The class definition [1] is adopted to define a concept, namely: a set of objects that share the same attributes, operations, relations, and semantics. The following concept types are specified: STANDARD CONCEPT: a concept that contains no further (sub ...
localizable metadata and data; Cubes is capable of handling large amounts of data and complex queries. According to a review by TechTarget, Cubes can handle "data volumes in the hundreds of millions of rows" and "complex queries and calculations that require multi-level aggregations and dynamic subsetting."
A good example of metadata is the cataloging system found in libraries, which records for example the author, title, subject, and location on the shelf of a resource. Another is software system knowledge extraction of software objects such as data flows, control flows, call maps, architectures, business rules, business terms, and database schemas.