EMAIL CLUSTERING AND GROUPING BASED ON CONTENT SIMILARITY USING K-MEANS ALGORITHM

INDRAKUSUMA, HUBERTUS VEGA (2018) EMAIL CLUSTERING AND GROUPING BASED ON CONTENT SIMILARITY USING K-MEANS ALGORITHM. Other thesis, Fakultas Teknik Informatika.

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Abstract

ABSTRACT Amount of email has been increasing dramatically as the growth of Internet, social media, and information management. Similarity measure of a group emails play an important role in email classification and clustering using K-means data clustering algorithm. K-means algorithm is one of many data clustering algorithm techniques. To overcome these problems Eucledian calculation also needed to do the data clustering. Grouped emails inside of different clusters based on the email similarities will become the final result of this project. Keyword: K-means, email classification, data clustering, eucledian

Item Type: Thesis (Other)
Subjects: 000 Computer Science, Information and General Works > 005 Computer programming, programs & data > Information Systems
Divisions: Faculty of Computer Science > Department of Information Systems
Depositing User: Mr Lucius Oentoeng
Date Deposited: 21 Jun 2018 03:37
Last Modified: 21 Jun 2018 03:37
URI: http://repository.unika.ac.id/id/eprint/16104

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