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Document classification based on kNN algorithm by term vector space reduction

Classification (of information); Data handling; Data mining; Information retrieval systems; Learning algorithms; Text processing; Vectors; Document Classification; Space reductions; Text classifiers; Text mining; Textual data; Unstructured data; Vector spaces

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Bibliographic Details
Main Authors: Moldagulova A., Sulaiman R.B.
Other Authors: 57160071400
Format: Conference Paper
Published: IEEE Computer Society 2023
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spelling my.uniten.dspace-234992023-05-29T14:49:57Z Document classification based on kNN algorithm by term vector space reduction Moldagulova A. Sulaiman R.B. 57160071400 25825633600 Classification (of information); Data handling; Data mining; Information retrieval systems; Learning algorithms; Text processing; Vectors; Document Classification; Space reductions; Text classifiers; Text mining; Textual data; Unstructured data; Vector spaces Nowadays there is an increasing interest in the area of unstructured data analysis. The vast majority of unstructured data belongs to unstructured text data. Retrieving useful information from huge volume of unstructured text data is very challenging task. Text mining is a thought-provoking research area as it tries to discover knowledge from unstructured text. This paper deals with methods used for handling unstructured text data in particular document classification problems. Most document classification methods based on term vector space model of representation of unstructured textual data. The term vector space model is easy to implement, provides uniform representation for documents. However feature space for a large collection of documents can reach millions and be sparse. One of the issues is to reduce the dimension of the term-document matrix. In this research we proposed an approach for reduction of term vector space in KNN algorithm. � ICROS. Final 2023-05-29T06:49:56Z 2023-05-29T06:49:56Z 2018 Conference Paper 2-s2.0-85060480043 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85060480043&partnerID=40&md5=d52c11efb08aee7a1a10a37b9778cd46 https://irepository.uniten.edu.my/handle/123456789/23499 2018-October 8571540 387 391 IEEE Computer Society Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description Classification (of information); Data handling; Data mining; Information retrieval systems; Learning algorithms; Text processing; Vectors; Document Classification; Space reductions; Text classifiers; Text mining; Textual data; Unstructured data; Vector spaces
author2 57160071400
author_facet 57160071400
Moldagulova A.
Sulaiman R.B.
format Conference Paper
author Moldagulova A.
Sulaiman R.B.
spellingShingle Moldagulova A.
Sulaiman R.B.
Document classification based on kNN algorithm by term vector space reduction
author_sort Moldagulova A.
title Document classification based on kNN algorithm by term vector space reduction
title_short Document classification based on kNN algorithm by term vector space reduction
title_full Document classification based on kNN algorithm by term vector space reduction
title_fullStr Document classification based on kNN algorithm by term vector space reduction
title_full_unstemmed Document classification based on kNN algorithm by term vector space reduction
title_sort document classification based on knn algorithm by term vector space reduction
publisher IEEE Computer Society
publishDate 2023
_version_ 1806428126053400576
score 13.214268

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