SOM Clustering Method Using User’s Features to Classify Profitable Customer for Recommender Service in u-Commerce

2015 ◽  
pp. 219-227
Author(s):  
Young Sung Cho ◽  
Song Chul Moon ◽  
Keun Ho Ryu
Keyword(s):  
Clustering Method ◽  
Som Clustering ◽  
Recommender Service

An Improving Algorithm Based on SOM Clustering and its Applications

2013 ◽  
Vol 655-657 ◽  
pp. 1000-1004
Author(s):  
Chen Guang Yan ◽  
Yu Jing Liu ◽  
Jin Hui Fan
Keyword(s):  
Data Clustering ◽  
Clustering Algorithm ◽  
Network Clustering ◽  
Self Organizing Map ◽  
Clustering Method ◽  
Map Algorithm ◽  
Som Neural Network ◽  
Simulation Results ◽  
Som Clustering ◽  
Selection Of

SOM (Self-organizing Map) algorithm is a clustering method basing on non-supervision condition. The paper introduces an improved algorithm based on SOM neural network clustering. It proposes SOM’s basic theory on data clustering. For SOM’s practical problems in applications, the algorithm also improved the selection of initial weights and the scope of neighborhood parameters. Finally, the simulation results in Matlab prove that the improved clustering algorithm improve the correct rate and computational efficiency of data clustering and to make the convergence speed better.

scholarly journals Dengue Disease Detection using K- Means, Hierarchical, Kohonen- SOM Clustering

2019 ◽  
Vol 8 (10) ◽  
pp. 904-907
Keyword(s):  
Data Mining ◽  
Clustering Algorithm ◽  
Research Work ◽  
Data Mining Algorithm ◽  
Clustering Method ◽  
Dengue Disease ◽  
Related Data ◽  
Som Algorithm ◽  
Som Clustering ◽  
Kohonen Som

Data Mining is the process of extracting useful information. Data Mining is about finding new information from pre-existing databases. It is the procedure of mining facts from data and deals with the kind of patterns that can be mined. Therefore, this proposed work is to detect and categorize the illness of people who are affected by Dengue through Data Mining techniques mainly as the Clustering method. Clustering is the method of finding related groups of data in a dataset and used to split the related data into a group of sub-classes. So, in this research work clustering method is used to categorize the age group of people those who are affected by mosquito-borne viral infection using K-Means and Hierarchical Clustering algorithm and Kohonen-SOM algorithm has been implemented in Tanagra tool. The scientists use the data mining algorithm for preventing and defending different diseases like Dengue disease. This paper helps to apply the algorithm for clustering of Dengue fever in Tanagra tool to detect the best results from those algorithms.

Hybrid of SOM-Clustering Method and Wavelet-ANFIS Approach to Model and Infill Missing Groundwater Level Data

2016 ◽  
Vol 21 (9) ◽  
pp. 05016018 ◽  
Author(s):  
Vahid Nourani ◽  
Mohammad Taghi Alami ◽  
Farnaz Daneshvar Vousoughi
Keyword(s):  
Groundwater Level ◽  
Clustering Method ◽  
Level Data ◽  
Som Clustering
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