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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| Format: | Journal |
| Language: | en |
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Elsevier Publications
2014
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| 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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| author | Imtiaz, Sharjeel Saadiah, Yahya |
| author_facet | Imtiaz, Sharjeel Saadiah, Yahya |
| author_sort | Imtiaz, Sharjeel |
| building | AEU Library |
| collection | Institutional Repository |
| content_provider | Asia e University |
| content_source | AEU University Repository |
| continent | Asia |
| country | Malaysia |
| 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 |
| id | my-aeu-eprints.526 |
| institution | Asia e University |
| language | en |
| publishDate | 2014 |
| publisher | Elsevier Publications |
| record_format | eprints |
| 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). |
| spellingShingle | T Technology (General) Imtiaz, Sharjeel Saadiah, Yahya A Patent Technique of Jaccard Discrete (J-DIS) Similarity Clustering Algorithm |
| title | 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_short | A Patent Technique of Jaccard Discrete (J-DIS) Similarity Clustering Algorithm |
| title_sort | patent technique of jaccard discrete (j-dis) similarity clustering algorithm |
| topic | T Technology (General) |
| url | http://ur.aeu.edu.my/526/1/A%20PatentTechnique%20of%20Jaccard%20DiscreteJ-DIS%20Similarity%20Clustering%20Algorithm.pdf http://ur.aeu.edu.my/526/ |
| url_provider | http://ur.aeu.edu.my/ |