Difference between revisions of "Enhancing Cluster Labeling Using Wikipedia"

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Enhancing Cluster Labeling Using Wikipedia
David Carmel
Haggai Roitman
Naama Zwerdling
Publication date

Enhancing Cluster Labeling Using Wikipedia - scientific work related to Wikipedia quality published in 2009, written by David Carmel, Haggai Roitman and Naama Zwerdling.


This work investigates cluster labeling enhancement by utilizing Wikipedia, the free on-line encyclopedia. Authors describe a general framework for cluster labeling that extracts candidate labels from Wikipedia in addition to important terms that are extracted directly from the text. The "labeling quality" of each candidate is then evaluated by several independent judges and the top evaluated candidates are recommended for labeling. Authors experimental results reveal that the Wikipedia labels agree with manual labels associated by humans to a cluster, much more than with significant terms that are extracted directly from the text. Authors show that in most cases even when human's associated label appears in the text, pure statistical methods have difficulty in identifying them as good descriptors. Furthermore, experiments show that for more than 85% of the clusters in test collection, the manual label (or an inflection, or a synonym of it) appears in the top five labels recommended by system.


Wikipedia Quality

Carmel, David; Roitman, Haggai; Zwerdling, Naama. (2009). "[[Enhancing Cluster Labeling Using Wikipedia]]".DOI: 10.1145/1571941.1571967.

English Wikipedia

{{cite journal |last1=Carmel |first1=David |last2=Roitman |first2=Haggai |last3=Zwerdling |first3=Naama |title=Enhancing Cluster Labeling Using Wikipedia |date=2009 |doi=10.1145/1571941.1571967 |url=https://wikipediaquality.com/wiki/Enhancing_Cluster_Labeling_Using_Wikipedia}}


Carmel, David; Roitman, Haggai; Zwerdling, Naama. (2009). &quot;<a href="https://wikipediaquality.com/wiki/Enhancing_Cluster_Labeling_Using_Wikipedia">Enhancing Cluster Labeling Using Wikipedia</a>&quot;.DOI: 10.1145/1571941.1571967.