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The objective of keyword research is to generate, with good precision and recall, a large number of terms that are highly relevant yet non-obvious to the given input keyword. [1] The process of keyword research involves brainstorming and the use of keyword research tools, with popular ones including Semrush and Google Trends.
According to Rev. Gerard O'Connor's Concordantia et Indices Missalium Romanorum, "Most of the concordances produced in recent times and with the aid of computer software use both the KWIC (keyword in context) and KWICn (keyword in center) formats, which lists the keyword, usually highlighted in bold text in a consistent position, within a ...
Tag cloud of a mailing list [1] A tag cloud with terms related to Web 2.0. A tag cloud (also known as a word cloud or weighted list in visual design) is a visual representation of text data which is often used to depict keyword metadata on websites, or to visualize free form text.
Keyword assignment methods can be roughly divided into: keyword assignment (keywords are chosen from controlled vocabulary or taxonomy) and; keyword extraction (keywords are chosen from words that are explicitly mentioned in original text). Methods for automatic keyword extraction can be supervised, semi-supervised, or unsupervised. [4]
Lexical tokenization is conversion of a text into (semantically or syntactically) meaningful lexical tokens belonging to categories defined by a "lexer" program. In case of a natural language, those categories include nouns, verbs, adjectives, punctuations etc.
Abstractive summarization methods generate new text that did not exist in the original text. [12] This has been applied mainly for text. Abstractive methods build an internal semantic representation of the original content (often called a language model), and then use this representation to create a summary that is closer to what a human might express.