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Exploiting site-level information to improve web search
2010
Proceedings of the 19th ACM international conference on Information and knowledge management - CIKM '10
Ranking Web search results has long evolved beyond simple bag-of-words retrieval models. Modern search engines routinely employ machine learning ranking that relies on exogenous relevance signals. Yet the majority of current methods still evaluate each Web page out of context. In this work, we introduce a novel source of relevance information for Web search by evaluating each page in the context of its host Web site. For this purpose, we devise two strategies for compactly representing entire
doi:10.1145/1871437.1871630
dblp:conf/cikm/BroderGJMMW10
fatcat:x44x3lgfgzhjxnenengtx2nkuu