Using KNN algorithm for classification of textual documents

Aiman Moldagulova, Rosnafisah Sulaiman

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Citations (Scopus)

Abstract

Nowadays the exponential growth of generation of textual documents and the emergent need to structure them increase the attention to the automated classification of documents into predefined categories. There is wide range of supervised learning algorithms that deal with text classification. This paper deals with an approach for building a machine learning system in R that uses K-Nearest Neighbors (KNN) method for the classification of textual documents. The experimental part of the research was done on collected textual documents from two sources: http://egov.kz and http://www.government.kz. The experiment was devoted to challenging thing of the KNN algorithm that to find the proper value of k which represents the number of neighbors.

Original languageEnglish
Title of host publicationICIT 2017 - 8th International Conference on Information Technology, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages665-671
Number of pages7
ISBN (Electronic)9781509063321
DOIs
Publication statusPublished - 20 Oct 2017
Event8th International Conference on Information Technology, ICIT 2017 - Amman, Jordan
Duration: 17 May 201718 May 2017

Other

Other8th International Conference on Information Technology, ICIT 2017
CountryJordan
CityAmman
Period17/05/1718/05/17

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Health Informatics
  • Information Systems and Management
  • Computer Networks and Communications
  • Computer Science Applications

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    Moldagulova, A., & Sulaiman, R. (2017). Using KNN algorithm for classification of textual documents. In ICIT 2017 - 8th International Conference on Information Technology, Proceedings (pp. 665-671). [8079924] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICITECH.2017.8079924