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Python sets are very much like mathematical sets, and support operations like set intersection and union. Python also features a frozenset class for immutable sets, see Collection types. Dictionaries (class dict) are mutable mappings tying keys and corresponding values. Python has special syntax to create dictionaries ({key: value})
Trie data structures are commonly used in predictive text or autocomplete dictionaries, and approximate matching algorithms. [11] Tries enable faster searches, occupy less space, especially when the set contains large number of short strings, thus used in spell checking , hyphenation applications and longest prefix match algorithms.
Methods on objects are functions attached to the object's class; the syntax instance. method (argument) is, for normal methods and functions, syntactic sugar for Class. method (instance, argument). Python methods have an explicit self parameter to access instance data, in contrast to the implicit self (or this) in some other object-oriented ...
The program can create a complete text representation of any group of objects by calling these methods, which are almost always already implemented in the base associative array class. [ 23 ] For programs that use very large data sets, this sort of individual file storage is not appropriate, and a database management system (DB) is required.
Lesk algorithm is a classical algorithm for word sense disambiguation introduced by Michael E. Lesk in 1986. [1] It operates on the premise that words within a given context are likely to share a common meaning.
A dictionary coder, also sometimes known as a substitution coder, is a class of lossless data compression algorithms which operate by searching for matches between the text to be compressed and a set of strings contained in a data structure (called the 'dictionary') maintained by the encoder. When the encoder finds such a match, it substitutes ...
Languages without a return statement, such as standard Pascal don't have this problem. Some languages, such as C++ and Python, employ concepts which allow actions to be performed automatically upon return (or exception throw) which mitigates some of these issues – these are often known as "try/finally" or similar.
It then compares each word with a known list of correctly spelled words (i.e. a dictionary). This might contain just a list of words, or it might also contain additional information, such as hyphenation points or lexical and grammatical attributes. An additional step is a language-dependent algorithm for handling morphology.