0% Complete
Home
/
11th International Conference on Computer and Knowledge Engineering
Detecting Non-Spherical Clusters Using Modified CURE Algorithm
Authors :
Arezou Safdari
1
Pedram Salehpour
2
1- University of Tabriz Electrical & Computer Engineering department
2- University of Tabriz Electrical & Computer Engineering department
Keywords :
CURE, hierarchical clustering, cluster center, clustering algorithm
Abstract :
Clustering using representatives (CURE) algorithm is a robust hierarchical clustering algorithm which is dealing with noise and outliers. CURE algorithm merges and divides the clusters in some datasets which are not separate enough or have density difference between them. The obtained results show that CURE clustering is sensitive to input parameters. In this paper, the advantages of density-based cluster center detection are represented, and a modified CURE clustering algorithm is developed. The new algorithm determines the cluster centers and doesn't allow merging the clusters which contain cluster centers in data points. Experimental results show that the proposed algorithm has the capability to extract clusters more efficiently than the traditional CURE algorithm.
Papers List
List of archived papers
Hybrid navigation based on GPS data and SIFT-based place recognition using Biologically-inspired SLAM
Sahar Salimpour Kasebi - Hadi Seyedarabi - Javad Musevi Niya
EEMC: Energy Efficient Multi-Clustering Using Grey Wolf Optimizer in WSNs
Maryam Ghorbanvirdi - Sayyed Majid Mazinani
To Transfer or Not To Transfer (TNT): Action Recognition in Still Image Using Transfer Learning
Ali Soltani Nezhad - Hojat Asgarian Dehkordi - Seyed Sajad Ashrafi - Shahriar Baradaran Shokouhi
A Comparative Analysis of Clinical Note Categories for Mortality Prediction in ICU Patients
Maryam Karrabi - Mohsen Kahani - Mina Afzali - Nadieh Armin
SingAll: Scalable Control Flow Checking for Multi-Process Embedded Systems
Mehdi Amininasab - Ahmad Patooghy - Mahdi Fazeli
VVC-AAR: Adaptive Attention-Aware Resolution and Residual Coding for Perceptually Optimized Ultra-Low Bitrate VVC Compression
Yaghoub Saberi - Somayeh Arab Najafabadi - Mohammadreza Hemmati
Developing Convolutional Neural Networks using a Novel Lamarckian Co-Evolutionary Algorithm
Zaniar Sharifi - Khabat Soltanian - Ali Amiri
ParsHomo: A T5-Powered Approach to High-Precision Persian Homograph Disambiguation
Hasan Jalali - Taha Mohaddesi
Systematic review on AI techniques in detection and navigation of agricultural machines and robots
Afsaneh Soleimani - Mohammad Boghrati - Hossein Damavandi
Early detection of Parkinson’s disease using Convolutional Neural Networks on SPECT images
Reyhaneh Dehghan - Marjan Naderan - Seyyed Enayatallah Alavi
more
Samin Hamayesh - Version 44.5.0