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DATASCIENCE
2007

Detecting Family Resemblance: Automated Genre Classification

11 years 6 months ago
Detecting Family Resemblance: Automated Genre Classification
This paper presents results in automated genre classification of digital documents in PDF format. It describes genre classification as an important ingredient in contextualising scientific data and in retrieving targetted material for improving research. The current paper compares the role of visual layout, stylistic features, and language model features in clustering documents and presents results in retrieving five selected genres (Scientific Article, Thesis, Periodicals, Business Report, and Form) from a pool of materials populated with documents of the nineteen most popular genres found in our experimental data set.
Yunhyong Kim, Seamus Ross
Added 13 Dec 2010
Updated 13 Dec 2010
Type Journal
Year 2007
Where DATASCIENCE
Authors Yunhyong Kim, Seamus Ross
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