Authors :
Indumathi A , Perumal P
Volume/Issue :
Volume 3 - 2018, Issue 2 - February
Google Scholar :
https://goo.gl/DF9R4u
Scribd :
https://goo.gl/SnA6Y6
Thomson Reuters ResearcherID :
https://goo.gl/3bkzwv
Abstract :
Now a day’s dealing with a tremendous measure of digital data in computerized form is essential in text mining applications. Text classification is a method of naturally arranging an arrangement of reports into classes from a predefined set. A noteworthy trademark or trouble of Text classification is high dimensionality of highlight space. The decrease of dimensionality by choosing new qualities which is subset of old properties is known as highlight determination. Highlight determination techniques are examined in this paper for lessening the dimensionality of the dataset by expelling highlights that are viewed as insignificant for the arrangement. In this paper we talk about a few methodologies of Text mining, highlight determination techniques and uses of Text order. The issue of characterization has been broadly examined in the data mining, machine learning, database, and data recovery groups with applications in various assorted spaces, for example, target promoting, restorative analysis, news aggregate separating, and report association. In this paper we have given an overview of a wide assortment of text classification algorithms.
Now a day’s dealing with a tremendous measure of digital data in computerized form is essential in text mining applications. Text classification is a method of naturally arranging an arrangement of reports into classes from a predefined set. A noteworthy trademark or trouble of Text classification is high dimensionality of highlight space. The decrease of dimensionality by choosing new qualities which is subset of old properties is known as highlight determination. Highlight determination techniques are examined in this paper for lessening the dimensionality of the dataset by expelling highlights that are viewed as insignificant for the arrangement. In this paper we talk about a few methodologies of Text mining, highlight determination techniques and uses of Text order. The issue of characterization has been broadly examined in the data mining, machine learning, database, and data recovery groups with applications in various assorted spaces, for example, target promoting, restorative analysis, news aggregate separating, and report association. In this paper we have given an overview of a wide assortment of text classification algorithms.