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Sort the lists of symbols according to frequency, with the most frequently occurring symbols at the left and the least common at the right. Divide the list into two parts, with the total frequency counts of the left part being as close to the total of the right as possible.
An abstract syntax tree (AST) is a data structure used in computer science to represent the structure of a program or code snippet. It is a tree representation of the abstract syntactic structure of text (often source code) written in a formal language. Each node of the tree denotes a construct occurring in the text.
In information retrieval, tf–idf (also TF*IDF, TFIDF, TF–IDF, or Tf–idf), short for term frequency–inverse document frequency, is a measure of importance of a word to a document in a collection or corpus, adjusted for the fact that some words appear more frequently in general. [1]
(For example, upon encountering a variable declaration, user-written code could save the name and type of the variable into an external data structure, so that these could be checked against later variable references detected by the parser.)
A simple and inefficient way to see where one string occurs inside another is to check at each index, one by one. First, we see if there is a copy of the needle starting at the first character of the haystack; if not, we look to see if there's a copy of the needle starting at the second character of the haystack, and so forth.
Below are some examples of operations with buffer gaps. The gap is represented by the empty space between the square brackets. This representation is a bit misleading: in a typical implementation, the endpoints of the gap are tracked using pointers or array indices, and the contents of the gap are ignored; this allows, for example, deletions to be done by adjusting a pointer without changing ...
A bigram or digram is a sequence of two adjacent elements from a string of tokens, which are typically letters, syllables, or words.A bigram is an n-gram for n=2.. The frequency distribution of every bigram in a string is commonly used for simple statistical analysis of text in many applications, including in computational linguistics, cryptography, and speech recognition.
Find the most frequently occurring substrings of a minimum length in () time. Find the shortest strings from Σ {\displaystyle \Sigma } that do not occur in D {\displaystyle D} , in O ( n + z ) {\displaystyle O(n+z)} time, if there are z {\displaystyle z} such strings.