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122
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CIKM
2010
Springer
14 years 11 months ago
Exploiting site-level information to improve web search
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 r...
Andrei Z. Broder, Evgeniy Gabrilovich, Vanja Josif...
111
Voted
CIKM
2011
Springer
14 years 10 days ago
A probabilistic method for inferring preferences from clicks
Evaluating rankers using implicit feedback, such as clicks on documents in a result list, is an increasingly popular alternative to traditional evaluation methods based on explici...
Katja Hofmann, Shimon Whiteson, Maarten de Rijke
103
Voted
WWW
2007
ACM
16 years 1 months ago
Query-driven indexing for peer-to-peer text retrieval
We describe a query-driven indexing framework for scalable text retrieval over structured P2P networks. To cope with the bandwidth consumption problem that has been identified as ...
Gleb Skobeltsyn, Toan Luu, Karl Aberer, Martin Raj...
112
Voted
WWW
2006
ACM
16 years 1 months ago
Optimizing scoring functions and indexes for proximity search in type-annotated corpora
We introduce a new, powerful class of text proximity queries: find an instance of a given "answer type" (person, place, distance) near "selector" tokens matchi...
Soumen Chakrabarti, Kriti Puniyani, Sujatha Das
91
Voted
WWW
2004
ACM
16 years 1 months ago
Web-scale information extraction in knowitall: (preliminary results)
Manually querying search engines in order to accumulate a large body of factual information is a tedious, error-prone process of piecemeal search. Search engines retrieve and rank...
Oren Etzioni, Michael J. Cafarella, Doug Downey, S...