عنوان المقالة:A Dynamic Linkage Clustering using KD-Tree
شادي إبراهيم أبوضلفة | Shadi Abudalfa | 5564
- نوع النشر
- مجلة علمية
- المؤلفون بالعربي
- Shadi Abudalfa, Mohammad Mikki
- الملخص العربي
- Some clustering algorithms calculate connectivity of each data point to its cluster by depending on density reachability. These algorithms can find arbitrarily shaped clusters, but they require parameters that are mostly sensitive to clustering performance. We develop a new dynamic linkage clustering algorithm using kd-tree. The proposed algorithm does not require any parameters and does not have a worst-case bound on running time that exists in many similar algorithms in the literature. Experimental results are shown in this paper to demonstrate the effectiveness of the proposed algorithm. We compare the proposed algorithm with other famous similar algorithm that is shown in literature. We present the proposed algorithm and its performance in detail along with promising avenues of future research.
- تاريخ النشر
- 01/05/2013
- الناشر
- The International Arab Journal of Information Technology (IAJIT)
- رابط الملف
- تحميل (161 مرات التحميل)
- رابط خارجي
- http://ccis2k.org/iajit/PDF/vol.10,no.3/11-4246.pdf
- الكلمات المفتاحية
- Data clustering, density-based clustering algorithm, KD-tree, dynamic linkage clustering, DBSCAN.