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Reciprocal rank fusion outperforms condorcet and individual rank learning methods

Gordon V. Cormack, Charles L A Clarke, Stefan Buettcher
2009 Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval - SIGIR '09  
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 better results than the standard  ...  method Condorcet Fuse.  ...  RECIPROCAL RANK FUSION While supervised learning-to-rank methods have garnered much attention of late, unsupervised methods are attractive because they require no training examples.  ... 
doi:10.1145/1571941.1572114 dblp:conf/sigir/CormackCB09 fatcat:nyidmye5ivdipbxgeroe2iv5ae

Ranking Model Selection and Fusion for Effective Microblog Search [chapter]

Zhongyu Wei, Wei Gao, Tarek El-Ganainy, Walid Magdy, Kam-Fai Wong
2017 Social Media Content Analysis  
We explore the use of query-sensitive model selection and rank fusion methods based on the result lists produced from multiple rank learners.  ...  Base on the TREC microblog datasets, we found that our selection-based ensemble approach can significantly outperform using the single best ranker, and it also has clear advantage over the rank fusion  ...  Borda-all, Condorcet-all, and RRF-all: Combine all the eight available candidate rankers using CombMNZ, weighted Borda-fuse, and weighed Condorcet-fuse, and Reciprocal Rank Fusion, respectively; (5) CMNZ-sel  ... 
doi:10.1142/9789813223615_0001 fatcat:7dm4pizfsvf3rc76hom4yulwju

Ranking model selection and fusion for effective microblog search

Zhongyu Wei, Wei Gao, Tarek El-Ganainy, Walid Magdy, Kam-Fai Wong
2014 Proceedings of the first international workshop on Social media retrieval and analysis - SoMeRA '14  
We explore the use of query-sensitive model selection and rank fusion methods based on the result lists produced from multiple rank learners.  ...  Base on the TREC microblog datasets, we found that our selection-based ensemble approach can significantly outperform using the single best ranker, and it also has clear advantage over the rank fusion  ...  Borda-all, Condorcet-all, and RRF-all: Combine all the eight available candidate rankers using CombMNZ, weighted Borda-fuse, and weighed Condorcet-fuse, and Reciprocal Rank Fusion, respectively; (5) CMNZ-sel  ... 
doi:10.1145/2632188.2632202 dblp:conf/sigir/WeiGEMW14 fatcat:o7bakyacdjf4dcfff62szevcce

Learning to rank academic experts in the DBLP dataset

Catarina Moreira, Pável Calado, Bruno Martins
2013 Expert systems  
More specifically, this article explores the use of supervised learning to rank methods, as well as rank aggregation approaches, for combing all of the estimators of expertise.  ...  Several supervised learning algorithms, which are representative of the pointwise, pairwise and listwise approaches, were tested, and various state-of-the-art data fusion techniques were also explored  ...  On the other hand, the Condorcet Fusion algorithm outperformed all of the other methods in almost all of the evaluation metrics tested.  ... 
doi:10.1111/exsy.12062 fatcat:kvteq7ck6bfo3aewtdbtkafefm

Learning to rank by aggregating expert preferences

Maksims N. Volkovs, Hugo Larochelle, Richard S. Zemel
2012 Proceedings of the 21st ACM international conference on Information and knowledge management - CIKM '12  
When applied to crowdsourcing and meta-search benchmarks, our new algorithm improves on state-of-the-art preference aggregation methods.  ...  Specifically, we describe how such problems can be converted into a standard learning-to-rank one on which existing learning solutions can be invoked.  ...  We also compare with the established meta-search standards Condorcet and Reciprocal Rank Fusion (RRF) as well as the Bradley-Terry and Plackett-Luce models and the SVD-based method SVP.  ... 
doi:10.1145/2396761.2396868 dblp:conf/cikm/VolkovsLZ12 fatcat:y2sgypmmjnfwhhluq2qtm44vt4

A multimodal tensor-based late fusion approach for satellite image search in Sentinel 2 images

Ilias Gialampoukidis, Anastasia Moumtzidou, Marios Bakratsas, Stefanos Vrochidis, Ioannis Kompatsiaris
2021 Zenodo  
Quantitative and qualitative results show that the proposed method outperforms search by a single modality and other late fusion methods.  ...  We propose a late fusion mechanism of multiple rankings to combine the results from several uni-modal searches in Sentinel 2 image collections.  ...  Acknowledgements This work was supported by the EC-funded projects H2020-832876-aqua3S and H2020-776019-EOPEN.  ... 
doi:10.5281/zenodo.4293265 fatcat:lqibjpr27zbyljyz3um53xciny

Unsupervised ensemble ranking of terms in electronic health record notes based on their importance to patients

Jinying Chen, Hong Yu
2017 Journal of Biomedical Informatics  
Targeted education can then be developed to improve patient EHR comprehension and the quality of care.  ...  One way to help patients is to reduce information overload and help them focus on medical terms that matter most to them.  ...  We thank the UMassMed annotation team, including Elaine Freund, Victoria Wang, Andrew Hsu, Barinder Hansra and Sonali Harchandani, for creating the evaluation corpus and thank Weisong Liu for technical  ... 
doi:10.1016/j.jbi.2017.02.016 pmid:28267590 pmcid:PMC5505865 fatcat:utxgm2xqh5cpxbazuyogw5pbki

2020 Deep Learning Track

Tiago Almeida, Sérgio Matos
2020 Text Retrieval Conference  
We describe a two-stage retrieval pipeline for the TREC Deep Learning 2020 track, where we used a lightweight neural model to rerank a baseline produced by an efficient traditional technique.  ...  for Science and Technology, in the context of the project UIDB/00127/2020.  ...  Acknowledgments This work has received support from the EU/EFPIA Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 806968 and from National Funds through the FCT -Foundation  ... 
dblp:conf/trec/AlmeidaM20 fatcat:bj2m3uxaq5ftvfnkb66g5gylty

Search result diversification via data fusion

Shengli Wu, Chunlan Huang
2014 Proceedings of the 37th international ACM SIGIR conference on Research & development in information retrieval - SIGIR '14  
In this short paper, we propose a few data fusion methods to try to improve performance when both relevance and diversity are concerned.  ...  Experiments are carried out with 3 groups of top-ranked results submitted to the TREC web diversity task.  ...  CombSum, CombMNZ, and the Condorcet method belong to the first category, while the linear combination method is a representative of the second category.  ... 
doi:10.1145/2600428.2609451 dblp:conf/sigir/WuH14 fatcat:yhze4v3uxbbzdfbr4xucoum6gq

CRF framework for supervised preference aggregation

Maksims N. Volkovs, Richard S. Zemel
2013 Proceedings of the 22nd ACM international conference on Conference on information & knowledge management - CIKM '13  
Experiments on benchmark tasks demonstrate significant performance gains over existing rank aggregation methods.  ...  We describe procedures for learning in this model and demonstrate that inference can be done much more efficiently than in analogous models.  ...  In addition, we compare with the established meta-search standards Condorcet Fusion [27] and Reciprocal Rank Fusion (RRF) [8] as well as the Plackett-Luce model.  ... 
doi:10.1145/2505515.2505713 dblp:conf/cikm/VolkovsZ13 fatcat:gojj4loxxratrakpyvzlcdoxfm

Ranks Aggregation and Semantic Genetic Approach based Hybrid Model for Query Expansion

Jagendra Singh
2017 International Journal of Computational Intelligence Systems  
However, it is always a challenging task to find an individual expansion terms selection method that would outperform other individual methods in most cases.  ...  Fourth, the Genetic Algorithm used to make an optimal combination of query terms and candidate expansion terms obtained by applying ranks combination and semantic filtering approach.  ...  However, it remains as a challenge to develop an individual terms selection method that would outperform other methods in most cases.  ... 
doi:10.2991/ijcis.2017.10.1.4 fatcat:cme2zofzpzdpblsfjgol3klb2i

An Optimization Framework for Merging Multiple Result Lists

Chia-Jung Lee, Qingyao Ai, W. Bruce Croft, Daniel Sheldon
2015 Proceedings of the 24th ACM International on Conference on Information and Knowledge Management - CIKM '15  
In the experiments on collection fusion and data fusion, the proposed approach significantly outperforms several standard baselines and state-of-the-art learning-based approaches.  ...  Developing effective methods for fusing multiple ranked lists of documents is crucial to many applications.  ...  Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect those of the sponsor.  ... 
doi:10.1145/2806416.2806489 dblp:conf/cikm/LeeACS15 fatcat:t63cqqlgy5hjtb7ow7zqbav2ci

Top-kdominant web services under multi-criteria matching

Dimitrios Skoutas, Dimitris Sacharidis, Alkis Simitsis, Verena Kantere, Timos Sellis
2009 Proceedings of the 12th International Conference on Extending Database Technology Advances in Database Technology - EDBT '09  
Since there is no consensus on how to weight these scores, existing methods are typically pessimistic, adopting a worst-case scenario.  ...  Second, the reduction of individual scores to an overall similarity leads to significant information loss.  ...  The Condorcet-fuse method [31] is another rank-based fusion approach.  ... 
doi:10.1145/1516360.1516463 dblp:conf/edbt/SkoutasSSKS09 fatcat:scfut5y2qrcmppsgwltnjw6i2y

Preference-based Online Learning with Dueling Bandits: A Survey [article]

Viktor Bengs, Robert Busa-Fekete, Adil El Mesaoudi-Paul, Eyke Hüllermeier
2021 arXiv   pre-print
In machine learning, the notion of multi-armed bandits refers to a class of online learning problems, in which an agent is supposed to simultaneously explore and exploit a given set of choice alternatives  ...  Our taxonomy is mainly based on the assumptions made by these methods about the data-generating process and, related to this, the properties of the preference-based feedback.  ...  Acknowledgments Eyke Hüllermeier, Adil El Mesaoudi-Paul and Viktor Bengs gratefully acknowledge financial support by the German Research Foundation (DFG).  ... 
arXiv:1807.11398v2 fatcat:jsu6gap5pbgbtm735fgf4aqwmu

Preference-based Online Learning with Dueling Bandits: A Survey

Viktor Bengs, Róbert Busa-Fekete, Adil El Mesaoudi-Paul, Eyke Hüllermeier
2021 Journal of machine learning research  
In machine learning, the notion of multi-armed bandits refers to a class of online learning problems, in which an agent is supposed to simultaneously explore and exploit a given set of choice alternatives  ...  Our taxonomy is mainly based on the assumptions made by these methods about the datagenerating process and, related to this, the properties of the preference-based feedback.  ...  Acknowledgments Eyke Hüllermeier, Adil El Mesaoudi-Paul and Viktor Bengs gratefully acknowledge financial support by the German Research Foundation (DFG).  ... 
dblp:journals/jmlr/BengsBMH21 fatcat:mdxi3bzymrb37ckbxbh27pu6f4
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