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» A Probability Model for Combining Ranks
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ML
2010
ACM
141views Machine Learning» more  ML 2010»
14 years 10 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 5 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»
15 years 12 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 15 days 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»
14 years 11 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...