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Vector space model
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Vector space model : ウィキペディア英語版
Vector space model
Vector space model or term vector model is an algebraic model for representing text documents (and any objects, in general) as vectors of identifiers, such as, for example, index terms. It is used in information filtering, information retrieval, indexing and relevancy rankings. Its first use was in the SMART Information Retrieval System.
==Definitions==

Documents and queries are represented as vectors.
:d_j = ( w_ ,w_ , \dotsc ,w_ )
:q = ( w_ ,w_ , \dotsc ,w_ )
Each dimension corresponds to a separate term. If a term occurs in the document, its value in the vector is non-zero. Several different ways of computing these values, also known as (term) weights, have been developed. One of the best known schemes is tf-idf weighting (see the example below).
The definition of ''term'' depends on the application. Typically terms are single words, keywords, or longer phrases. If words are chosen to be the terms, the dimensionality of the vector is the number of words in the vocabulary (the number of distinct words occurring in the corpus).
Vector operations can be used to compare documents with queries.

抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)
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