Analysis of initialization method on fuzzy c-means algorithm based on singular value decomposition for topic detection

Ichsani Mursidah, Hendri Murfi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Citations (Scopus)

Abstract

Topic detection is the process of finding the topics in a document collection. For a large amount of dataset, manual topic detection is difficult or even impossible. Thus, we need an automatic method known as Topic Detection and Tracking (TDT). One of the TDT methods used for topic detection problem is a clustering-based method such as fuzzy C-means (FCM). FCM works reasonably well on low-dimensional data but fails on high-dimensional data. In the high-dimensional data, a random-based initialization of FCM converges to one cluster center called center of gravity, so that all topics generated are similar. In this paper, we examine a non-random initialization by using singular value decomposition (SVD). Our simulations show that the SVD-based initialization method solves the center of gravity problem in a certain degree of fuzziness and gives a better accuracy than the random-based initialization.

Original languageEnglish
Title of host publicationProceedings - 2017 1st International Conference on Informatics and Computational Sciences, ICICoS 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages213-217
Number of pages5
ISBN (Electronic)9781538609033
DOIs
Publication statusPublished - 30 Jan 2018
Event1st International Conference on Informatics and Computational Sciences, ICICoS 2017 - Semarang, Indonesia
Duration: 15 Nov 201716 Nov 2017

Publication series

NameProceedings - 2017 1st International Conference on Informatics and Computational Sciences, ICICoS 2017
Volume2018-January

Conference

Conference1st International Conference on Informatics and Computational Sciences, ICICoS 2017
Country/TerritoryIndonesia
CitySemarang
Period15/11/1716/11/17

Keywords

  • clustering
  • fuzzy c-means
  • initialization
  • Singular Value Decomposition
  • topic detection

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