Ranking very many typed entities on wikipedia. Zaragoza, H., Rode, H., Mika, P., Atserias, J., Ciaramita, M., & Attardi, G. Proceedings of the sixteenth ACM conference on Conference on information and knowledge management CIKM 07, ACM Press, 2007.
Website abstract bibtex 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.
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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.},
bibtype = {article},
author = {Zaragoza, Hugo and Rode, Henning and Mika, Peter and Atserias, Jordi and Ciaramita, Massimiliano and Attardi, Giuseppe},
journal = {Proceedings of the sixteenth ACM conference on Conference on information and knowledge management CIKM 07}
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