Skip to main content
Article thumbnail
Location of Repository

A SURVEY OF TEXT CLUSTERING ALGORITHMS

By Charu C. Aggarwal and ChengXiang Zhai

Abstract

Clustering is a widely studied data mining problem in the text domains. The problem finds numerous applications in customer segmentation, classification, collaborative filtering, visualization, document organization, and indexing. In this chapter, we will provide a detailed survey of the problem of text clustering. We will study the key challenges of the clustering problem, as it applies to the text domain. We will discuss the key methods used for text clustering, and their relative advantages. We will also discuss a number of recent advances in the area in the context of social network and linked data.

Topics: Text Clustering
Publisher: 2013-12-09
Year: 2012
OAI identifier: oai:CiteSeerX.psu:10.1.1.352.3280
Provided by: CiteSeerX
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • http://citeseerx.ist.psu.edu/v... (external link)
  • http://link.springer.com/conte... (external link)
  • Suggested articles


    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.