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Using kNN model for automatic text categorization

Authors:

Kieran GreerAuthors Info & Claims

Soft Computing - A Fusion of Foundations, Methodologies and Applications, Volume 10, Issue 5

Pages 423 - 430

https://doi.org/10.1007/s00500-005-0503-y

Published: 01 March 2006 Publication History

Abstract

An investigation is conducted on two well-known similarity-based learning approaches to text categorization: the k-nearest neighbors (kNN) classifier and the Rocchio classifier. After identifying the weakness and strength of each technique, a new classifier called the kNN model-based classifier (kNN Model) is proposed. It combines the strength of both kNN and Rocchio. A text categorization prototype, which implements kNN Model along with kNN and Rocchio, is described. An experimental evaluation of different methods is carried out on two common document corpora: the 20-newsgroup collection and the ModApte version of the Reuters-21578 collection of news stories. The experimental results show that the proposed kNN model-based method outperforms the kNN and Rocchio classifiers, and is therefore a good alternative for kNN and Rocchio in some application areas.

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Cited By

Mustafi DMustafi A(2023)A differential evolution based algorithm to cluster text corpora using lazy re-evaluation of fringe pointsMultimedia Tools and Applications10.1007/s11042-023-14716-382:21(32177-32201)Online publication date: 2-Mar-2023
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Li JLin SYu KGuo G(2022)Quantum K-nearest neighbor classification algorithm based on Hamming distanceQuantum Information Processing10.1007/s11128-021-03361-021:1Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1007/s11128-021-03361-0
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Using kNN model for automatic text categorization
1. Computing methodologies
  1. Machine learning
    1. Learning paradigms
      1. Supervised learning
    2. Machine learning approaches

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cover image Soft Computing - A Fusion of Foundations, Methodologies and Applications

Soft Computing - A Fusion of Foundations, Methodologies and Applications Volume 10, Issue 5

March 2006

64 pages

ISSN:1432-7643

EISSN:1433-7479

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Copyright © Copyright © 2006 Springer-Verlag Berlin Heidelberg.

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Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 01 March 2006

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Cited By

Mustafi DMustafi A(2023)A differential evolution based algorithm to cluster text corpora using lazy re-evaluation of fringe pointsMultimedia Tools and Applications10.1007/s11042-023-14716-382:21(32177-32201)Online publication date: 2-Mar-2023
https://dl.acm.org/doi/10.1007/s11042-023-14716-3
Li JLin SYu KGuo G(2022)Quantum K-nearest neighbor classification algorithm based on Hamming distanceQuantum Information Processing10.1007/s11128-021-03361-021:1Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1007/s11128-021-03361-0
Li LPeltsverger SZheng JLe LHandlin MLunt BHansen DMorrey P(2021)Retrieving and Classifying LinkedIn Job Titles for Alumni Career AnalysisProceedings of the 22nd Annual Conference on Information Technology Education10.1145/3450329.3476858(85-90)Online publication date: 6-Oct-2021
https://dl.acm.org/doi/10.1145/3450329.3476858
Liu CWang WTu GXiang YWang SLv F(2017)A new Centroid-Based Classification model for text categorizationKnowledge-Based Systems10.5555/3170714.3170794136:C(15-26)Online publication date: 15-Nov-2017
https://dl.acm.org/doi/10.5555/3170714.3170794
Georgieva-Trifonova T(2017)Text Classification Based on Enriched Vector Space ModelProceedings of the 18th International Conference on Computer Systems and Technologies10.1145/3134302.3134343(103-110)Online publication date: 23-Jun-2017
https://dl.acm.org/doi/10.1145/3134302.3134343
Guo NHe YYan CLiu LWang CJiang CRana OAntonopoulos N(2016)Multi-level topical text categorization with wikipediaProceedings of the 9th International Conference on Utility and Cloud Computing10.1145/2996890.3007856(343-352)Online publication date: 6-Dec-2016
https://dl.acm.org/doi/10.1145/2996890.3007856
Chen LYe YGuo GZhu J(2016)Kernel-based linear classification on categorical dataSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-015-1926-820:8(2981-2993)Online publication date: 1-Aug-2016
https://dl.acm.org/doi/10.1007/s00500-015-1926-8
Brand DKroon Svan der Merwe BCleophas L(2015)N-Gram Representations For Comment FilteringProceedings of the 2015 Annual Research Conference on South African Institute of Computer Scientists and Information Technologists10.1145/2815782.2815789(1-10)Online publication date: 28-Sep-2015
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Chemchem ADrias H(2015)From data mining to knowledge miningExpert Systems with Applications: An International Journal10.1016/j.eswa.2014.08.02442:3(1436-1445)Online publication date: 15-Feb-2015
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Pang GJin HJiang S(2015)CenKNNData Mining and Knowledge Discovery10.1007/s10618-014-0358-x29:3(593-625)Online publication date: 1-May-2015
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