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» A Probability Model for Combining Ranks
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ML
2010
ACM
141views Machine Learning» more  ML 2010»
15 years 2 months ago
Relational retrieval using a combination of path-constrained random walks
Scientific literature with rich metadata can be represented as a labeled directed graph. This graph representation enables a number of scientific tasks such as ad hoc retrieval o...
Ni Lao, William W. Cohen
SIGIR
2006
ACM
15 years 9 months ago
Using historical data to enhance rank aggregation
Rank aggregation is a pervading operation in IR technology. We hypothesize that the performance of score-based aggregation may be affected by artificial, usually meaningless devia...
Miriam Fernández, David Vallet, Pablo Caste...
VLDB
2008
ACM
196views Database» more  VLDB 2008»
16 years 4 months ago
Modelling retrieval models in a probabilistic relational algebra with a new operator: the relational Bayes
This paper presents a probabilistic relational modelling (implementation) of the major probabilistic retrieval models. Such a high-level implementation is useful since it supports ...
Thomas Rölleke, Hengzhi Wu, Jun Wang, Hany Azzam
ICML
2007
IEEE
16 years 4 months ago
Learning to rank: from pairwise approach to listwise approach
The paper is concerned with learning to rank, which is to construct a model or a function for ranking objects. Learning to rank is useful for document retrieval, collaborative fil...
Zhe Cao, Tao Qin, Tie-Yan Liu, Ming-Feng Tsai, Han...
SIAMSC
2008
148views more  SIAMSC 2008»
15 years 3 months ago
Multilevel Adaptive Aggregation for Markov Chains, with Application to Web Ranking
A multilevel adaptive aggregation method for calculating the stationary probability vector of an irreducible stochastic matrix is described. The method is a special case of the ada...
Hans De Sterck, Thomas A. Manteuffel, Stephen F. M...