A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2009; you can also visit the original URL.
The file type is application/pdf.
Filters
Reciprocal rank fusion outperforms condorcet and individual rank learning methods
2009
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval - SIGIR '09
Preserved Fulltext
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]
2017
Social Media Content Analysis
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
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
2014
Proceedings of the first international workshop on Social media retrieval and analysis - SoMeRA '14
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
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
2013
Expert systems
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
Other Versions
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
2012
Proceedings of the 21st ACM international conference on Information and knowledge management - CIKM '12
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2015; you can also visit the original URL.
The file type is application/pdf.
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
2021
Zenodo
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
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
2017
Journal of Biomedical Informatics
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Other Versions
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
2020
Text Retrieval Conference
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
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
2014
Proceedings of the 37th international ACM SIGIR conference on Research & development in information retrieval - SIGIR '14
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
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
2013
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management - CIKM '13
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2014; you can also visit the original URL.
The file type is application/pdf.
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
2017
International Journal of Computational Intelligence Systems
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
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
2015
Proceedings of the 24th ACM International on Conference on Information and Knowledge Management - CIKM '15
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
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
2009
Proceedings of the 12th International Conference on Extending Database Technology Advances in Database Technology - EDBT '09
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
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]
2021
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Other Versions
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
2021
Journal of machine learning research
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
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
« Previous
Showing results 1 — 15 out of 36 results