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In computer science, the Knuth–Morris–Pratt algorithm (or KMP algorithm) is a string-searching algorithm that searches for occurrences of a "word" W within a main "text string" S by employing the observation that when a mismatch occurs, the word itself embodies sufficient information to determine where the next match could begin, thus bypassing re-examination of previously matched characters.
In this example, we will consider a dictionary consisting of the following words: {a, ab, bab, bc, bca, c, caa}. The graph below is the Aho–Corasick data structure constructed from the specified dictionary, with each row in the table representing a node in the trie, with the column path indicating the (unique) sequence of characters from the root to the node.
A string-searching algorithm, sometimes called string-matching algorithm, is an algorithm that searches a body of text for portions that match by pattern. A basic example of string searching is when the pattern and the searched text are arrays of elements of an alphabet ( finite set ) Σ.
Word2vec is a technique in natural language processing (NLP) for obtaining vector representations of words. These vectors capture information about the meaning of the word based on the surrounding words.
Onomatopoeia: a word or a grouping of words that imitates the sound it is describing; Phonetic reversal; Rhyme: a repetition of identical or similar sounds in two or more different words Alliteration: matching consonants sounds at the beginning of words; Assonance: matching vowel sounds; Consonance: matching consonant sounds
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The raw input, the 43 characters, must be explicitly split into the 9 tokens with a given space delimiter (i.e., matching the string " "or regular expression /\s{1}/). When a token class represents more than one possible lexeme, the lexer often saves enough information to reproduce the original lexeme, so that it can be used in semantic analysis .
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