Open AccessA Recapitulation of Different Text Classification Algorithms
Author(s) -
B Riya
Publication year - 2020
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.e6550.038620
Subject(s) - computer science , categorization , text categorization , process (computing) , content (measure theory) , information retrieval , natural language processing , term (time) , data mining , artificial intelligence , order (exchange) , mathematics , mathematical analysis , physics , finance , quantum mechanics , economics , operating system
Text classification process has gained a lot of importance in recent years and is still one of the most popular topics of discussion because of the presence of a huge outsized range of electronic documents from diverse resources. The text categorization process assigns predefined classes to documents. It finds noteworthy similarities in large textual data were interesting, hidden, previously unknown and extremely useful patterns and information can be discovered. Text classification helps in analysis of large textual data. Text mining intends facilitating customers extract informations from resources, and deals with operations such as retrieving, classifying ,cluster formation, mining of data, processing of natural language and techniques of machine learning together to classificate unalike patterns. Inside the process of content arrangement, terms gauging strategies configuration fitting loads to the offered terms to improvise content grouping execution. This paper overviews content order, the procedure of content grouping, distinctive term gauging techniques and correlations between various characterization calculations.