Encyclopedia of Database Systems

2018 Edition
| Editors: Ling Liu, M. Tamer Özsu

Text Clustering

Reference work entry
DOI: https://doi.org/10.1007/978-1-4614-8265-9_415


Text clustering is to automatically group textual documents (for example, documents in plain text, web pages, emails and etc) into clusters based on their content similarity. The problem of text clustering can be defined as follows. Given a set of n documents noted as DS and a pre-defined cluster number K (usually set by users), DS is clustered into K document clusters DS1 , DS2 , … , DSk, (i . e , {DS1, DS2, … , DSk} = DS) so that the documents in a same document cluster are similar to one another while documents from different clusters are dissimilar [14].

Historical Background

Text clustering was initially developed to improve the performance of search engines through pre-clustering the entire corpus [2]. Text clustering later has also been investigated as a post-retrieval document browsing technique [1, 2, 7].


Text clustering consists of several important components including document representation, text clustering algorithms and performance measurements....

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Microsoft Research AsiaBeijingChina

Section editors and affiliations

  • Zheng Chen
    • 1
  1. 1.Microsoft Research AsiaMicrosoft CorporationBeijingChina