Text Clustering Algorithm: Difference between revisions

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===2009===
===2009===
* ([[2009_ExploitingWikipediaAsExter|Hu & al, 1999]]) ⇒ [[Xiaohua Hu]], Xiaodan Zhang, Caimei Lu, E. K. Park, and Xiaohua Zhou. ([[2009]]). "Exploiting Wikipedia as External Knowledge for Document Clustering." In: Proceedings of [[ACM SIGKDD]] Conference ([[KDD 2009]]). [http://dx.doi.org/10.1145/1557019.1557066 doi:10.1145/1557019.1557066]
* ([[2009_ExploitingWikipediaAsExternalKn|Hu & al, 1999]]) ⇒ [[Xiaohua Hu]], Xiaodan Zhang, Caimei Lu, E. K. Park, and Xiaohua Zhou. ([[2009]]). "Exploiting Wikipedia as External Knowledge for Document Clustering." In: Proceedings of [[ACM SIGKDD]] Conference ([[KDD 2009]]). [http://dx.doi.org/10.1145/1557019.1557066 doi:10.1145/1557019.1557066]


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===2008===

Revision as of 07:43, 13 January 2015

A Text Clustering Algorithm is a domain specific clustering algorithm that can solve the text clustering task.



References

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  • (Steinbach, 2000) ⇒ Michael Steinbach, George Karypis, and Vipin Kumar. (2000). "A Comparison of Document Clustering Techniques." In: Proceedings of Workshop at KDD 2000 on Text Mining.
    • We use two metrics for evaluating cluster quality: entropy, which provides a measure of “goodness” for un-nested clusters or for the clusters at one level of a hierarchical clustering, and the F-measure, which measures the effectiveness of a hierarchical clustering. (The F measure was recently extended to document hierarchies in [5].)

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