Year: 2012
Type: conference-paper
Abstract: There is a demand for taxonomies to organise large collections of documents into categories for browsing and exploration. This paper examines four existing taxonomies that have been manually created, along with two methods for deriving taxonomies automatically from data items. We use these taxonomies to organise items from a large online cultural heritage collection. We then present two human evaluations of the taxonomies. The first measures the cohesion of the taxonomies to determine how well they group together similar items under the same concept node. The second analyses the concept relations in the taxonomies. The results show that the manual taxonomies have high quality well defined relations. However the novel automatic method is found to generate very high cohesion
Authors: Samuel Fernando, Mark Hall, Eneko Agirre, Aitor Soroa, Paul Clough, Mark Stevenson
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W13564052