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Word2vec can use either of two model architectures to produce these distributed representations of words: continuous bag of words (CBOW) or continuously sliding skip-gram. In both architectures, word2vec considers both individual words and a sliding context window as it iterates over the corpus.
In mathematical terms, an associative array is a function with finite domain. [1] It supports 'lookup', 'remove', and 'insert' operations. The dictionary problem is the classic problem of designing efficient data structures that implement associative arrays. [2] The two major solutions to the dictionary problem are hash tables and search trees.
Here is a non-exhaustive list of typical items found in a data dictionary for columns or fields: Entity or form name or their ID (EntityID or FormID). The group this field belongs to. Field name, such as RDBMS field name; Displayed field title. May default to field name if blank. Field type (string, integer, date, etc.)
Map is sometimes generalized to accept dyadic (2-argument) functions that can apply a user-supplied function to corresponding elements from two lists. Some languages use special names for this, such as map2 or zipWith. Languages using explicit variadic functions may have versions of map with variable arity to support variable-arity functions ...
The rationale is that passing an (x,y,z) record to a function that expects an (x,y) record as argument should work, since that function will find all the fields it requires within the record. Many ways of practically implementing records in programming languages would have trouble with allowing such variability, but the matter is a central ...
Given two different words of the same length, say a = a 1 a 2...a k and b = b 1 b 2...b k, the order of the two words depends on the alphabetic order of the symbols in the first place i where the two words differ (counting from the beginning of the words): a < b if and only if a i < b i in the underlying order of the alphabet A.
Natural language processing (NLP) is a subfield of computer science and especially artificial intelligence.It is primarily concerned with providing computers with the ability to process data encoded in natural language and is thus closely related to information retrieval, knowledge representation and computational linguistics, a subfield of linguistics.
An entity–attribute–value model (EAV) is a data model optimized for the space-efficient storage of sparse—or ad-hoc—property or data values, intended for situations where runtime usage patterns are arbitrary, subject to user variation, or otherwise unforeseeable using a fixed design.