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A thesaurus is composed by at least three elements: 1-a list of words (or terms), 2-the relationship amongst the words (or terms), indicated by their hierarchical relative position (e.g. parent/broader term; child/narrower term, synonym, etc.), 3-a set of rules on how to use the thesaurus.
Another common example is "RAM memory", which is redundant because "RAM" ("random-access memory") includes the initial of the word "memory". "PIN" stands for "personal identification number", obviating the second word in " PIN number"; in this case its retention may be motivated to avoid ambiguity with the homophonous word "pin".
A thesaurus (pl.: thesauri or thesauruses), sometimes called a synonym dictionary or dictionary of synonyms, is a reference work which arranges words by their meanings (or in simpler terms, a book where one can find different words with similar meanings to other words), [1] [2] sometimes as a hierarchy of broader and narrower terms, sometimes simply as lists of synonyms and antonyms.
However, older English exonyms are sometimes used in certain contexts, for example: Peking (Beijing; duck, opera, etc.), Tsingtao (Qingdao), and Canton (Guangdong). In some cases the traditional English exonym is based on a local Chinese variety instead of Mandarin, in the case of Xiamen, where the name Amoy is closer to the Hokkien pronunciation.
For example, in written text each symbol or letter conveys information relevant to the word it is part of, each word conveys information relevant to the phrase it is part of, each phrase conveys information relevant to the sentence it is part of, and so on until at the final step information is interpreted and becomes knowledge in a given domain.
Semantics studies meaning in language, which is limited to the meaning of linguistic expressions. It concerns how signs are interpreted and what information they contain. An example is the meaning of words provided in dictionary definitions by giving synonymous expressions or paraphrases, like defining the meaning of the term ram as adult male sheep. [22]
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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. The word2vec algorithm estimates these representations by modeling text in a large corpus.