Calculating distance measure for clustering in multi-relational settings
published: Oct. 30, 2013, recorded: October 2013, views: 1765
Report a problem or upload filesIf you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
The paper deals with a distance based multi-relational clustering application in a real data case study. A novel method for a dissimilarity matrix calculation in multi-relational settings has been proposed and implemented in R language. The proposed method has been tested by analyzing public actions related to data mining subject and indexed in the medical index database MedLine. Clustering based on partitioning around methods was used for the semi-automated identification of the most popular topics among the MedLine publications. The algorithm implements greedy approach and is suitable for small data sets with a limited number of 1:n relational joins.
Download slides: sikdd2013_niaksu_multirelational_settings_01.pdf (1.8 MB)
Link this pageWould you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !