A Patent Technique of Jaccard Discrete (J-DIS) Similarity Clustering Algorithm

A Patent Technique of Jaccard Discrete (J-DIS) Similarity Clustering Algorithm

Traditionally, the classification object yields homogeneous object to separate cluster. Few authors investigated clustering based on k-Means to distinguish intrusions based on the particular class. Mostly, k-Means algorithm finds out similarity between the object based on distance vector for smalles...

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Main Authors: Imtiaz, Sharjeel, Saadiah, Yahya
Format: Journal
Language:English
Published: Elsevier Publications 2014
Subjects:
T Technology (General)
Online Access:http://ur.aeu.edu.my/526/1/A%20PatentTechnique%20of%20Jaccard%20DiscreteJ-DIS%20Similarity%20Clustering%20Algorithm.pdf
http://ur.aeu.edu.my/526/
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Language: English
id my-aeu-eprints.526
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spelling my-aeu-eprints.5262019-06-24T03:44:48Z http://ur.aeu.edu.my/526/ A Patent Technique of Jaccard Discrete (J-DIS) Similarity Clustering Algorithm Imtiaz, Sharjeel Saadiah, Yahya T Technology (General) Traditionally, the classification object yields homogeneous object to separate cluster. Few authors investigated clustering based on k-Means to distinguish intrusions based on the particular class. Mostly, k-Means algorithm finds out similarity between the object based on distance vector for smallest dataset. We proposed a new approach Jaccard Discrete (J-DIS) based approach which is combines with k-Means to find most similar measures over features attribute values in a larger dataset. Further, this paper is describing best suitable larger dataset taken from KDD CUP-99 dataset [1].Moreover, the J-DIS k-Means approach can be applied over clinical informatics and wireless clustering based routing protocols. Elsevier Publications 2014 Journal NonPeerReviewed text en http://ur.aeu.edu.my/526/1/A%20PatentTechnique%20of%20Jaccard%20DiscreteJ-DIS%20Similarity%20Clustering%20Algorithm.pdf Imtiaz, Sharjeel and Saadiah, Yahya (2014) A Patent Technique of Jaccard Discrete (J-DIS) Similarity Clustering Algorithm. Proceedings of the 2nd International Conference on Applied Information and Communications Technology (ICAICT 28-29 April 2014).
institution Asia e University
building AEU Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Asia e University
content_source AEU University Repository
url_provider http://ur.aeu.edu.my/
language English
topic T Technology (General)
spellingShingle T Technology (General)
Imtiaz, Sharjeel
Saadiah, Yahya
A Patent Technique of Jaccard Discrete (J-DIS) Similarity Clustering Algorithm
description Traditionally, the classification object yields homogeneous object to separate cluster. Few authors investigated clustering based on k-Means to distinguish intrusions based on the particular class. Mostly, k-Means algorithm finds out similarity between the object based on distance vector for smallest dataset. We proposed a new approach Jaccard Discrete (J-DIS) based approach which is combines with k-Means to find most similar measures over features attribute values in a larger dataset. Further, this paper is describing best suitable larger dataset taken from KDD CUP-99 dataset [1].Moreover, the J-DIS k-Means approach can be applied over clinical informatics and wireless clustering based routing protocols.
format Journal
author Imtiaz, Sharjeel
Saadiah, Yahya
author_facet Imtiaz, Sharjeel
Saadiah, Yahya
author_sort Imtiaz, Sharjeel
title A Patent Technique of Jaccard Discrete (J-DIS) Similarity Clustering Algorithm
title_short A Patent Technique of Jaccard Discrete (J-DIS) Similarity Clustering Algorithm
title_full A Patent Technique of Jaccard Discrete (J-DIS) Similarity Clustering Algorithm
title_fullStr A Patent Technique of Jaccard Discrete (J-DIS) Similarity Clustering Algorithm
title_full_unstemmed A Patent Technique of Jaccard Discrete (J-DIS) Similarity Clustering Algorithm
title_sort patent technique of jaccard discrete (j-dis) similarity clustering algorithm
publisher Elsevier Publications
publishDate 2014
url http://ur.aeu.edu.my/526/1/A%20PatentTechnique%20of%20Jaccard%20DiscreteJ-DIS%20Similarity%20Clustering%20Algorithm.pdf
http://ur.aeu.edu.my/526/
_version_ 1644539727305506816

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