Automatic combination of multiple ranked retrieval systems
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
Analyses of multiple evidence combination
Proceedings of the 20th annual international ACM SIGIR conference on Research and development in information retrieval
Predicting the performance of linearly combined IR systems
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Database merging strategy based on logistic regression
Information Processing and Management: an International Journal
Rank aggregation methods for the Web
Proceedings of the 10th international conference on World Wide Web
Modeling score distributions for combining the outputs of search engines
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Relevance score normalization for metasearch
Proceedings of the tenth international conference on Information and knowledge management
Condorcet fusion for improved retrieval
Proceedings of the eleventh international conference on Information and knowledge management
Fusion Via a Linear Combination of Scores
Information Retrieval
How to Make Stacking Better and Faster While Also Taking Care of an Unknown Weakness
ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning
From Retrieval Status Values to Probabilities of Relevance for Advanced IR Applications
Information Retrieval
Web metasearch: rank vs. score based rank aggregation methods
Proceedings of the 2003 ACM symposium on Applied computing
Improving high accuracy retrieval by eliminating the uneven correlation effect in data fusion
Journal of the American Society for Information Science and Technology
Combining schema and instance information for integrating heterogeneous data sources
Data & Knowledge Engineering
An outranking approach for rank aggregation in information retrieval
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Assigning appropriate weights for the linear combination data fusion method in information retrieval
Information Processing and Management: an International Journal
Generative model-based metasearch for data fusion in information retrieval
Proceedings of the 9th ACM/IEEE-CS joint conference on Digital libraries
Issues in stacked generalization
Journal of Artificial Intelligence Research
A signal-to-noise approach to score normalization
Proceedings of the 18th ACM conference on Information and knowledge management
Information extraction for search engines using fast heuristic techniques
Data & Knowledge Engineering
Image fusion based on a new contourlet packet
Information Fusion
Combining ontological profiles with context in information retrieval
Data & Knowledge Engineering
Segmentation of search engine results for effective data-fusion
ECIR'07 Proceedings of the 29th European conference on IR research
Estimating probabilities for effective data fusion
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
A late fusion approach to cross-lingual document re-ranking
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
A novel keyword search paradigm in relational databases: Object summaries
Data & Knowledge Engineering
Selecting the n-top retrieval result lists for an effective data fusion
CICLing'10 Proceedings of the 11th international conference on Computational Linguistics and Intelligent Text Processing
The weighted Condorcet fusion in information retrieval
Information Processing and Management: an International Journal
Extending information unit across media streams for improving retrieval effectiveness
Data & Knowledge Engineering
ExpertRank: A topic-aware expert finding algorithm for online knowledge communities
Decision Support Systems
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In information retrieval, data fusion (also known as meta-search) has been investigated by many researchers. Previous investigation and experimentation demonstrate that the linear combination method is an effective data fusion method for combining multiple information retrieval results. One advantage is its flexibility, since different weights can be assigned to different component systems so as to obtain better fusion results. The key issue is how to assign good weights to all the component retrieval systems involved. Surprisingly, research in this field is limited and it is still an open question. In this paper, we use the multiple linear regression technique with estimated relevance scores and judged scores to obtain suitable weights. Although the multiple linear regression technique is not new, the way of using it in this paper has never been attempted before for the data fusion problem in information retrieval. Our experiments with five groups of runs submitted to TREC show that the linear combination method with such a weighting strategy steadily outperforms the best component system and other data fusion methods including CombSum, CombMNZ, PosFuse, MAPFuse, SegFuse, and the linear combination method with performance level/performance square weighting schemes by large margins.