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Authors: A. K. M. Zahiduzzaman ; Mohammad Nahyan Quasem ; Faiyaz Ahmed and Rashedur M. Rahman

Affiliation: North South University, Bangladesh

Keyword(s): Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), Factor Analysis (FA), Intensification, c-Means clustering, Fuzzy c-Means clustering.

Related Ontology Subjects/Areas/Topics: Advanced Applications of Fuzzy Logic ; Applications of Expert Systems ; Artificial Intelligence ; Artificial Intelligence and Decision Support Systems ; Biomedical Engineering ; Data Engineering ; Data Mining ; Databases and Information Systems Integration ; Enterprise Information Systems ; Health Information Systems ; Information Systems Analysis and Specification ; Knowledge Management ; Ontologies and the Semantic Web ; Sensor Networks ; Signal Processing ; Society, e-Business and e-Government ; Soft Computing ; Web Information Systems and Technologies

Abstract: The paper presents two document clustering techniques to group Bangla newspaper articles. The first one is based on traditional c-means algorithm, and the later is based on its fuzzy counterpart, i.e., fuzzy c-means algorithm. The key principle for both of those techniques is to measure the frequency of keywords in a particular type of article to calculate the significance of those keywords. The articles are then clustered based on the significance of the keywords. We believe the findings from this research will help to index Bangla newspaper articles. Therefore, the information retrieval will be faster than before. However, one of the challenge is to find the salient features from hundred of features found in documents. Besides, both clustering algorithms work well on lower dimensions. To address this, we use three dimensionality reduction techniques, known as Principle Component Analysis (PCA), Factor Analysis (FA) and Linear Discriminant Analysis (LDA). We present and analyze the performance of traditional and fuzzy c-means algorithms with different dimensionality reduction techniques. (More)

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Paper citation in several formats:
K. M. Zahiduzzaman, A.; Nahyan Quasem, M.; Ahmed, F. and M. Rahman, R. (2011). INDEXING BANGLA NEWSPAPER ARTICLES USING FUZZY AND CRISP CLUSTERING ALGORITHMS. In Proceedings of the 13th International Conference on Enterprise Information Systems - Volume 2: ICEIS; ISBN 978-989-8425-53-9; ISSN 2184-4992, SciTePress, pages 361-364. DOI: 10.5220/0003492603610364

@conference{iceis11,
author={A. {K. M. Zahiduzzaman}. and Mohammad {Nahyan Quasem}. and Faiyaz Ahmed. and Rashedur {M. Rahman}.},
title={INDEXING BANGLA NEWSPAPER ARTICLES USING FUZZY AND CRISP CLUSTERING ALGORITHMS},
booktitle={Proceedings of the 13th International Conference on Enterprise Information Systems - Volume 2: ICEIS},
year={2011},
pages={361-364},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003492603610364},
isbn={978-989-8425-53-9},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the 13th International Conference on Enterprise Information Systems - Volume 2: ICEIS
TI - INDEXING BANGLA NEWSPAPER ARTICLES USING FUZZY AND CRISP CLUSTERING ALGORITHMS
SN - 978-989-8425-53-9
IS - 2184-4992
AU - K. M. Zahiduzzaman, A.
AU - Nahyan Quasem, M.
AU - Ahmed, F.
AU - M. Rahman, R.
PY - 2011
SP - 361
EP - 364
DO - 10.5220/0003492603610364
PB - SciTePress