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» A Probability Model for Combining Ranks
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SIGIR
2009
ACM
15 years 6 months ago
Reciprocal rank fusion outperforms condorcet and individual rank learning methods
Reciprocal Rank Fusion (RRF), a simple method for combining the document rankings from multiple IR systems, consistently yields better results than any individual system, and bett...
Gordon V. Cormack, Charles L. A. Clarke, Stefan B&...
ALDT
2011
Springer
200views Algorithms» more  ALDT 2011»
13 years 11 months ago
Vote Elicitation with Probabilistic Preference Models: Empirical Estimation and Cost Tradeoffs
A variety of preference aggregation schemes and voting rules have been developed in social choice to support group decision making. However, the requirement that participants provi...
Tyler Lu, Craig Boutilier
85
Voted
ACL
1994
15 years 1 months ago
Similarity-Based Estimation of Word Cooccurrence Probabilities
In many applications of natural language processing it is necessary to determine the likelihood of a given word combination. For example, a speech recognizer may need to determine...
Ido Dagan, Fernando C. N. Pereira, Lillian Lee
ENGL
2007
75views more  ENGL 2007»
14 years 11 months ago
Uncertainty Modeling for Expensive Functions: A Rank Transformation Approach
An uncertainty model for an expensive function greatly improves the effectiveness of a design decision based on the use of a less accurate function. In this paper, we propose a met...
J. Umakant, K. Sudhakar, P. M. Mujumdar, C. Raghav...
CIKM
2008
Springer
15 years 1 months ago
Ranked feature fusion models for ad hoc retrieval
We introduce the Ranked Feature Fusion framework for information retrieval system design. Typical information retrieval formalisms such as the vector space model, the bestmatch mo...
Jeremy Pickens, Gene Golovchinsky