Abstract
We discuss the problem of ranking very many entities of different types. In particular we deal with a heterogeneous set of types, some being very generic and some very specific. We discuss two approaches for this problem: i) exploiting the entity containment graph and ii) using a Web search engine to compute entity relevance. We evaluate these approaches on the real task of ranking Wikipedia entities typed with a state-of-the-art named-entity tagger. Results show that both approaches can greatly increase the performance of methods based only on passage retrieval.
Original language | Undefined |
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Title of host publication | Proceedings of the sixteenth ACM conference on Conference on information and knowledge management, CIKM '07 |
Place of Publication | New York, NY, USA |
Publisher | ACM Press |
Pages | 1015-1018 |
Number of pages | 4 |
ISBN (Print) | 978-1-59593-803-9 |
DOIs | |
Publication status | Published - Nov 2007 |
Event | 16th ACM conference on Conference on Information and Knowledge Management, CIKM 2007 - Lisbon, Portugal Duration: 6 Nov 2007 → 9 Nov 2007 Conference number: 16 |
Publication series
Name | |
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Publisher | ACM Press |
Number | FS-07-05 |
Conference
Conference | 16th ACM conference on Conference on Information and Knowledge Management, CIKM 2007 |
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Abbreviated title | CIKM |
Country/Territory | Portugal |
City | Lisbon |
Period | 6/11/07 → 9/11/07 |
Keywords
- EWI-11439
- CR-H.3.3
- METIS-245789
- IR-62024
- DB-XMLIR: XML INFORMATION RETRIEVAL