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[1] [2] In compiling a dictionary, a lexicographer decides whether the evidence of use is sufficient to justify an entry in the dictionary. This decision is not the same as determining whether the word exists. [citation needed] The green background means a given dictionary is the largest in a given language.
For example, one could define a dictionary having a string "toast" mapped to the integer 42 or vice versa. The keys in a dictionary must be of an immutable Python type, such as an integer or a string, because under the hood they are implemented via a hash function. This makes for much faster lookup times, but requires keys not change.
The intuition is that the closer two words or synsets are, the closer their meaning. A number of WordNet-based word similarity algorithms are implemented in a Perl package called WordNet::Similarity, [21] and in a Python package called NLTK. [22]
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 ...
The two characters commonly used for this purpose are the hyphen ("-") and the underscore ("_"); e.g., the two-word name "two words" would be represented as "two-words" or "two_words". The hyphen is used by nearly all programmers writing COBOL (1959), Forth (1970), and Lisp (1958); it is also common in Unix for commands and packages, and is ...
Wordnik, a nonprofit organization, is an online English dictionary and language resource that provides dictionary and thesaurus content. [1] Some of the content is based on print dictionaries such as the Century Dictionary, the American Heritage Dictionary, WordNet, and GCIDE.
It disregards word order (and thus most of syntax or grammar) but captures multiplicity. The bag-of-words model is commonly used in methods of document classification where, for example, the (frequency of) occurrence of each word is used as a feature for training a classifier. [1] It has also been used for computer vision. [2]
The database is distributed as a plain text file with one entry to a line in the format "WORD <pronunciation>" with a two-space separator between the parts. If multiple pronunciations are available for a word, variants are identified using numbered versions (e.g. WORD(1)).