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COLING
2010

Best Topic Word Selection for Topic Labelling

10 years 7 months ago
Best Topic Word Selection for Topic Labelling
This paper presents the novel task of best topic word selection, that is the selection of the topic word that is the best label for a given topic, as a means of enhancing the interpretation and visualisation of topic models. We propose a number of features intended to capture the best topic word, and show that, in combination as inputs to a reranking model, we are able to consistently achieve results above the baseline of simply selecting the highest-ranked topic word. This is the case both when training in-domain over other labelled topics for that topic model, and cross-domain, using only labellings from independent topic models learned over document collections from different domains and genres.
Jey Han Lau, David Newman, Sarvnaz Karimi, Timothy
Added 13 May 2011
Updated 13 May 2011
Type Journal
Year 2010
Where COLING
Authors Jey Han Lau, David Newman, Sarvnaz Karimi, Timothy Baldwin
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