Exploiting information needs and bibliographics for polyrepresentative document clustering
dc.contributor.author | Abbasi, Muhammad Kamran | en |
dc.contributor.author | Frommholz, Ingo | en |
dc.date.accessioned | 2014-10-24T11:13:09Z | |
dc.date.available | 2014-10-24T11:13:09Z | |
dc.date.issued | 2014-04 | |
dc.identifier.citation | Abbasi, M.K., Frommholz, I. (2014) 'Exploiting information needs and bibliographics for polyrepresentative document clustering', In Proceedings of the Bibliometrics-enhanced Information Retrieval Workshop at ECIR 2014, Amsterdam: 21–28 | en |
dc.identifier.issn | 1613-0073 | |
dc.identifier.uri | http://hdl.handle.net/10547/333127 | |
dc.description.abstract | In this paper we explore the potential of combining the principle of polyrepresentation with document clustering. Our idea is discussed and evaluated for polyrepresentation of information needs as wells as for document-based polyrepresentation where bibliographic information is used as representation. The main idea is to present the user with the highly ranked polyrepresentative clusters to support the search process. Our evaluation suggests that our approach is capable of increasing retrieval performance, but performance varies for queries with a high or low number of relevant documents. | |
dc.language.iso | en | en |
dc.publisher | CEUR-WS | en |
dc.relation.url | http://ceur-ws.org/Vol-1143/ | en |
dc.subject | polyrepresentation | en |
dc.subject | document clustering | en |
dc.subject | bibliographics | en |
dc.subject | information needs | en |
dc.subject | information retrieval | en |
dc.title | Exploiting information needs and bibliographics for polyrepresentative document clustering | en |
dc.type | Conference papers, meetings and proceedings | en |
dc.contributor.department | University of Bedfordshire | en |
dc.identifier.journal | Proceedings of the Bibliometrics-enhanced Information Retrieval Workshop at ECIR 2014 | en |
html.description.abstract | In this paper we explore the potential of combining the principle of polyrepresentation with document clustering. Our idea is discussed and evaluated for polyrepresentation of information needs as wells as for document-based polyrepresentation where bibliographic information is used as representation. The main idea is to present the user with the highly ranked polyrepresentative clusters to support the search process. Our evaluation suggests that our approach is capable of increasing retrieval performance, but performance varies for queries with a high or low number of relevant documents. |