Ranking under temporal constraints

13 years 4 months ago
Ranking under temporal constraints
This paper introduces the notion of temporally constrained ranked retrieval, which, given a query and a time constraint, produces the best possible ranked list within the specified time limit. Naturally, more time should translate into better results, but the ranking algorithm should always produce some results. This property is desirable from a number of perspectives: to cope with diverse users and information needs, as well as to better manage system load and variance in query execution times. We propose two temporally constrained ranking algorithms based on a class of probabilistic prediction models that can naturally incorporate efficiency constraints: one that makes independent feature selection decisions, and the other that makes joint feature selection decisions. Experiments on three different test collections show that both ranking algorithms are able to satisfy imposed time constraints, although the joint model outperforms the independent model in being able to deliver more...
Lidan Wang, Donald Metzler, Jimmy Lin
Added 24 Jan 2011
Updated 24 Jan 2011
Type Journal
Year 2010
Where CIKM
Authors Lidan Wang, Donald Metzler, Jimmy Lin
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