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Ranking very many typed entities on Wikipedia
Abstract We discuss the problem of ranking very manWe 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.f methods based only on passage retrieval.
Added by wikilit team Added on initial load  +
Collected data time dimension Cross-sectional  +
Comments " With respect to entity containment graph" With respect to entity containment graphs our results show that it is important to take into account the notion of inverted entity frequency to discount general types. With respect to Web methods we showed that taking into account the rank of the documents in the computation of correlations can yield signi cant improvements in performanc" p. 1018i cant improvements in performanc" p. 1018
Conclusion We have taken the rst steps towards studyWe have taken the rst steps towards studying the problem of ad-hoc entity ranking in the presence of a large set of heterogeneous entities. We have constructed a realistic test- bed to carry out evaluation of entity ranking models, and we have provided some initial directions of research. With respect to entity containment graphs our results show that it is important to take into account the notion of inverted entity frequency to discount general types. With respect to Web methods we showed that taking into account the rank of the documents in the computation of correlations can yield signi cant improvements in performanceeld signi cant improvements in performance
Data source Wikipedia pages  +
Google scholar url http://scholar.google.com/scholar?ie=UTF-8&q=%22Ranking%2Bvery%2Bmany%2Btyped%2Bentities%2Bon%2BWikipedia%22  +
Has author Hugo Zaragoza + , Henning Rode + , Peter Mika + , Jordi Atserias + , Massimiliano Ciaramita + , Giuseppe Attardi +
Has domain Computer science +
Has topic Ranking and clustering systems +
Pages 1015-1018  +
Peer reviewed Yes  +
Publication type Conference paper  +
Published in CIKM '07 Proceedings of the sixteenth ACM conference on Conference on information and knowledge management +
Research design Statistical analysis  +
Research questions 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.
Revid 10,921  +
Theories Undetermined
Theory type Design and action  +
Title Ranking very many typed entities on Wikipedia
Unit of analysis Article  +
Wikipedia coverage Main topic  +
Wikipedia data extraction Dump  +
Wikipedia language English  +
Wikipedia page type Article  +
Year 2007  +
Creation dateThis property is a special property in this wiki. 15 March 2012 20:30:01  +
Categories Ranking and clustering systems  + , Computer science  + , Publications  +
Modification dateThis property is a special property in this wiki. 30 January 2014 20:30:51  +
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