Open AccessDetecting Similarities in Posts Using Vector Space and Matrix
Author(s) -
Al Fataa Waliyyul Haq,
Ema Carinia,
Sudradjat Supian,
Subiyanto Subiyanto
Publication year - 2020
Publication title -
international journal of global operations research
Language(s) - English
Resource type - Journals
eISSN - 2723-1747
pISSN - 2722-1016
DOI - 10.47194/ijgor.v1i3.53
Subject(s) - vector space , matrix (chemical analysis) , vector space model , space (punctuation) , algebra over a field , similarity (geometry) , linear algebra , vector (molecular biology) , algebraic number , matrix algebra , matrix similarity , computer science , mathematics , pure mathematics , artificial intelligence , physics , mathematical analysis , eigenvalues and eigenvectors , geometry , biochemistry , chemistry , materials science , image (mathematics) , partial differential equation , composite material , gene , recombinant dna , operating system , quantum mechanics
This study discusses the application of two linear algebraic materials, namely vector and matrix spaces. The application of the two materials is related to an article, the writing can be in the form of an article, book, and so on. The writings examined in this study use example sentences made by the author. Two materials of linear algebra, namely the vector space and the matrix are used to analyze whether there is a similarity between the writing made with other writing. As a result, vector space and matrix can be used to detect similarities in a text.