dc.contributor.author | Medelyan, Olena | |
dc.contributor.author | Manion, Steve | |
dc.contributor.author | Broekstra, Jeen | |
dc.contributor.author | Divoli, Anna | |
dc.contributor.author | Huang, Anna-Lan | |
dc.contributor.author | Witten, Ian H. | |
dc.coverage.spatial | Conference held at Montpellier, France | en_NZ |
dc.date.accessioned | 2013-09-06T05:02:14Z | |
dc.date.available | 2013-09-06T05:02:14Z | |
dc.date.copyright | 2013 | |
dc.date.issued | 2013 | |
dc.identifier.citation | Medelyan, O., Manion, S., Broekstra, J., Divoli, A., Huang, A.-L., & Witten, I. H. (2013). Constructing a focused taxonomy from a document collection. In P. Cimiano et al. (Eds.): ESWC 2013, LNCS 7882 (pp. 367-381). Berlin, Germany: Springer-Verlag Berlin Heidelberg. | en_NZ |
dc.identifier.uri | https://hdl.handle.net/10289/7975 | |
dc.description.abstract | We describe a new method for constructing custom taxonomies from document collections. It involves identifying relevant concepts and entities in text; linking them to knowledge sources like Wikipedia, DBpedia, Freebase, and any supplied taxonomies from related domains; disambiguating conflicting concept mappings; and selecting semantic relations that best group them hierarchically. An RDF model supports interoperability of these steps, and also provides a flexible way of including existing NLP tools and further knowledge sources. From 2000 news articles we construct a custom taxonomy with 10,000 concepts and 12,700 relations, similar in structure to manually created counterparts. Evaluation by 15 human judges shows the precision to be 89% and 90% for concepts and relations respectively; recall was 75% with respect to a manually generated taxonomy for the same domain. | en_NZ |
dc.format.mimetype | application/pdf | |
dc.language.iso | en | en_NZ |
dc.publisher | Springer-Verlag Berlin Heidelberg | en_NZ |
dc.relation.uri | http://link.springer.com/chapter/10.1007%2F978-3-642-38288-8_25 | |
dc.rights | This is an author’s accepted version. The original publication is available at www.springerlink.com. | en_NZ |
dc.source | ESWC 2013 | en_NZ |
dc.subject | computer science | en_NZ |
dc.subject | Machine learning | |
dc.title | Constructing a focused taxonomy from a document collection | en_NZ |
dc.type | Conference Contribution | en_NZ |
dc.identifier.doi | 10.1007/978-3-642-38288-8_25 | en_NZ |
dc.relation.isPartOf | Proc 10th International Conference on the Semantic Web: Semantics and Big Data | en_NZ |
pubs.begin-page | 367 | en_NZ |
pubs.elements-id | 22944 | |
pubs.end-page | 381 | en_NZ |
pubs.finish-date | 2013-05-30 | en_NZ |
pubs.start-date | 2013-05-26 | en_NZ |
pubs.volume | LNCS 7882 | en_NZ |