Authors
Charu C Aggarwal, ChengXiang Zhai
Publication date
2012
Journal
Mining text data
Pages
77-128
Publisher
Springer US
Description
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.
Total citations
2012201320142015201620172018201920202021202220232024823626193108116948785936241
Scholar articles