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Enhancing cluster labeling using Wikipedia

23 bytes removed, 14:47, January 17, 2014
abstract fix
|added_by_wikilit_team=Added on initial load
|article_language=English
|abstract=This work investigates cluster labeling enhancement by utilizing Wikipedia, the free on-line encyclopedia. We 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. Our 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. We 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 our experiments show that for more than 85\% of the clusters in our test collection the manual label (or an inflection or a synonym of it) appears in the top five labels recommended by our system. Copyright 2009 {ACM.}"
|doi=10.1145/1571941.1571967
|gscites=14099639641125736698
|theories=Undetermined
|research_design=Experiment
|collected_datatype=Experiment responses, Archival records, Experiment responses, Wikipedia pages
|collected_data_time_dimension=Cross-sectional
|unit_of_analysis=Article