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» Rank-aware Query Optimization
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168
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NAACL
2010
15 years 4 months ago
Learning Dense Models of Query Similarity from User Click Logs
The goal of this work is to integrate query similarity metrics as features into a dense model that can be trained on large amounts of query log data, in order to rank query rewrit...
Fabio De Bona, Stefan Riezler, Keith Hall, Massimi...
SIGIR
2012
ACM
13 years 8 months ago
Active query selection for learning rankers
Methods that reduce the amount of labeled data needed for training have focused more on selecting which documents to label than on which queries should be labeled. One exception t...
Mustafa Bilgic, Paul N. Bennett
295
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ICDE
2007
IEEE
173views Database» more  ICDE 2007»
16 years 7 months ago
Top-k Query Processing in Uncertain Databases
Top-k processing in uncertain databases is semantically and computationally different from traditional top-k processing. The interplay between score and uncertainty makes traditio...
Mohamed A. Soliman, Ihab F. Ilyas, Kevin Chen-Chua...
GECCO
2007
Springer
283views Optimization» more  GECCO 2007»
16 years 9 days ago
Evolving Lucene search queries for text classification
We describe a method for generating accurate, compact, human understandable text classifiers. Text datasets are indexed using Apache Lucene and Genetic Programs are used to constr...
Laurence Hirsch, Robin Hirsch, Masoud Saeedi
EUROCAST
2005
Springer
102views Hardware» more  EUROCAST 2005»
15 years 11 months ago
Similarity Queries in Data Bases Using Metric Distances - from Modeling Semantics to Its Maintenance
Similarity queries in traditional databases work directly on attribute values. But, often similar attribute values do not indicate similar meanings. Semantic background information...
Josef Küng, Roland Wagner