Analyzing Fusion Methods Using the Condorcet Rule
Pages 2281 - 2285
Abstract
The fusion task is to merge document lists retrieved from a corpus for a query. We use the Condorcet voting rule to theoretically and empirically analyze fusion methods. We also demonstrate the merits of a novel fusion method based on a different voting rule: Copeland.
References
[1]
Yael Anava, Anna Shtok, Oren Kurland, and Ella Rabinovich. 2016. A Probabilistic Fusion Framework. In Proceedings of CIKM. 1463--1472.
[2]
Javed A. Aslam and Mark Montague. 2001. Models for metasearch. In Proceedings of SIGIR. 276--284.
[3]
Steven M. Beitzel, Eric C. Jensen, Abdur Chowdhury, Ophir Frieder, David A. Grossman, and Nazli Goharian. 2003. Disproving the Fusion Hypothesis: An Analysis of Data Fusion via Effective Information Retrieval Strategies. In Proceedings of SAC. 823--827.
[4]
Arthur H Copeland. 1951. A reasonable social welfare function. Technical Report. Mimeo, University of Michigan USA.
[5]
Gordon V. Cormack, Charles L. A. Clarke, and Stefan Büttcher. 2009. Reciprocal rank fusion outperforms condorcet and individual rank learning methods. In Proceedings of SIGIR. 758--759.
[6]
W. Bruce Croft. 2000. Combining approaches to information retrieval. In Advances in Information Retrieval: Recent Research from the Center for Intelligent Information Retrieval, W. Bruce Croft (Ed.). Kluwer.
[7]
J. C. de Borda. 1781. M'emoire sur les 'elections au scrutin. In Histoire de l'Academie Royale des Sciences.
[8]
M. de Condorcet. 1785. Essai sur l'application de l'analyse 'a la probabilit'e des decisions rendues 'a la pluralit'e des voix.
[9]
Peter C. Fishburn. 1974. Paradoxes of Voting. The American Political Science Review, Vol. 68, 2 (1974).
[10]
Edward A. Fox and Joseph A. Shaw. 1994. Combination of multiple searches. In Proceedings of TREC-2.
[11]
Jerry S. Kelly. 1988. Social Choice Theory: An Introduction. Springer-Verlag.
[12]
Anna Khudyak Kozorovitzky and Oren Kurland. 2011. From "Identical" to "Similar": Fusing Retrieved Lists Based on Inter-document Similarities. Journal of Artificial Intelligence Research, Vol. 41 (2011).
[13]
Mounia Lalmas. 2002. A Formal Model for Data Fusion. In Proceedings of FQAS. 274--288.
[14]
Chia-Jung Lee, Qingyao Ai, W. Bruce Croft, and Daniel Sheldon. 2015. An Optimization Framework for Merging Multiple Result Lists. In Proceedings of CIKM. 303--312.
[15]
Joon Ho Lee. 1995. Combining multiple evidence from different properties of weighting schemes. In Proceedings of SIGIR. 180--188.
[16]
Joon Ho Lee. 1997. Analyses of multiple evidence combination. In Proc. of SIGIR. 267--276.
[17]
David Lillis, Fergus Toolan, Rem W. Collier, and John Dunnion. 2006. ProbFuse: a probabilistic approach to data fusion. In Proceedings of SIGIR. 139--146.
[18]
David Lillis, Fergus Toolan, Rem W. Collier, and John Dunnion. 2008. Extending Probabilistic Data Fusion Using Sliding Windows. In Proceedings of ECIR. 358--369.
[19]
Mark Montague and Javed A. Aslam. 2002. Condorcet fusion for improved retrieval. In Proceedings of CIKM. 538--548.
[20]
Mark H. Montague and Javed A. Aslam. 2001. Relevance Score Normalization for Metasearch. In Proceedings CIKM. 427--433.
[21]
André Mour a o, Flá vio Martins, and Jo a o Magalh a es. 2014. Inverse square rank fusion for multimodal search. In 12th International Workshop on Content-Based Multimedia Indexing, CBMI. 1--6.
[22]
Haggai Roitman and Yosi Mass. 2019. Utilizing Passages in Fusion-based Document Retrieval. In Proceedings of ICTIR. 59--66.
[23]
Daniel Sheldon, Milad Shokouhi, Martin Szummer, and Nick Craswell. 2011. LambdaMerge: Merging the results of query reformulations. In Proceedings of WSDM. 795--804.
[24]
Milad Shokouhi. 2007. Segmentation of Search Engine Results for Effective Data-Fusion. In Proceedings of ECIR. 185--197.
[25]
Liron Tyomkin and Oren Kurland. 2023. Revisiting Condorcet Fusion. In Proceedings of SIGIR. 199--204.
[26]
Christopher C. Vogt and Garrison W. Cottrell. 1998. Predicting the Performance of Linearly Combined IR Systems. In Proceedings of SIGIR. 190--196.
[27]
Shengli Wu. 2009. Applying statistical principles to data fusion in information retrieval. Expert Systems with Applications, Vol. 36, 2 (2009), 2997--3006.
[28]
Shengli Wu. 2012. Data Fusion in Information Retrieval. Springer Publishing Company, Incorporated.
[29]
Shengli Wu. 2013. The weighted Condorcet fusion in information retrieval. Inf. Process. Manag., Vol. 49, 1 (2013), 108--122.
[30]
Shengli Wu and Fabio Crestani. 2015. A geometric framework for data fusion in information retrieval. Inf. Syst., Vol. 50 (2015), 20--35.
Index Terms
- Analyzing Fusion Methods Using the Condorcet Rule
Recommendations
Revisiting Condorcet Fusion
ICTIR '23: Proceedings of the 2023 ACM SIGIR International Conference on Theory of Information RetrievalThe fusion task is to aggregate ranked document lists retrieved for a query. The Condorcet voting criterion served as inspiration for a commonly used fusion method proposed by Montague and Aslam (2002). The method is stochastic as it is based on the ...
The weighted Condorcet fusion in information retrieval
The Condorcet fusion is a distinctive fusion method and was found useful in information retrieval. Two basic requirements for the Condorcet fusion to improve retrieval effectiveness are: (1) all component systems involved should be more or less equally ...
How Hard is Control in Multi-Peaked Elections: A Parameterized Study
AAMAS '15: Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent SystemsWe study the complexity of voting control problems in multi-peaked elections. In particular, we focus on the constructive/destructive control by adding/deleting votes under Condorcet, Maximin and Copelandα voting systems. We show that the NP of these ...
Comments
Information & Contributors
Information
Published In
July 2024
3164 pages
ISBN:9798400704314
DOI:10.1145/3626772
- General Chairs:
- Grace Hui Yang,
- Hongning Wang,
- Sam Han,
- Program Chairs:
- Claudia Hauff,
- Guido Zuccon,
- Yi Zhang
Copyright © 2024 Owner/Author.
This work is licensed under a Creative Commons Attribution International 4.0 License.
Sponsors
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 11 July 2024
Check for updates
Author Tags
Qualifiers
- Short-paper
Funding Sources
Conference
SIGIR 2024
Sponsor:
SIGIR 2024: The 47th International ACM SIGIR Conference on Research and Development in Information Retrieval
July 14 - 18, 2024
Washington DC, USA
Acceptance Rates
Overall Acceptance Rate 792 of 3,983 submissions, 20%
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 138Total Downloads
- Downloads (Last 12 months)138
- Downloads (Last 6 weeks)38
Reflects downloads up to 01 Jan 2025
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in