By Topic

Selection of features for surname classification

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)

We have studied the problem of classifying of surnames into the countries of origin using a collection of feature based learning algorithms. We have compiled a database of surnames and their countries of origin from publicly available databases as training data for the classifiers. We propose a feature selection algorithm which dynamically decides the most prominent feature of the names based on the training data. Based on the selected features, we utilized a number of supervised and unsupervised learning algorithms to classify the surnames into the countries. Finally, we have compared the accuracy and performance of the different classifiers with different parameters and metrics. We are able to demonstrate that the reduced feature set works well with the well-known classifiers.

Published in:

Information Reuse and Integration (IRI), 2011 IEEE International Conference on

Date of Conference:

3-5 Aug. 2011