Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
Probabilistic and genetic algorithms in document retrieval
Communications of the ACM
On term selection for query expansion
Journal of Documentation
A probabilistic learning approach for document indexing
ACM Transactions on Information Systems (TOIS) - Special issue on research and development in information retrieval
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
SIGIR '92 Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval
Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
ACM Transactions on Information Systems (TOIS)
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
Inferring probability of relevance using the method of logistic regression
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
Improving relevance feedback in the vector space model
CIKM '97 Proceedings of the sixth international conference on Information and knowledge management
Genetic programming: an introduction: on the automatic evolution of computer programs and its applications
Exploring the similarity space
ACM SIGIR Forum
An information-theoretic approach to automatic query expansion
ACM Transactions on Information Systems (TOIS)
Foundations of genetic programming
Foundations of genetic programming
Improving retrieval feedback with multiple term-ranking function combination
ACM Transactions on Information Systems (TOIS)
Fusion Via a Linear Combination of Scores
Information Retrieval
Ranking Function Optimization for Effective Web Search by Genetic Programming: An Empirical Study
HICSS '04 Proceedings of the Proceedings of the 37th Annual Hawaii International Conference on System Sciences (HICSS'04) - Track 4 - Volume 4
Enhanced web document retrieval using automatic query expansion
Journal of the American Society for Information Science and Technology
IEEE Transactions on Knowledge and Data Engineering
A generic ranking function discovery framework by genetic programming for information retrieval
Information Processing and Management: an International Journal
Optimization of some factors affecting the performance of query expansion
Information Processing and Management: an International Journal
Journal of the American Society for Information Science and Technology
Discretization based learning approach to information retrieval
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Re-examining the effects of adding relevance information in a relevance feedback environment
Information Processing and Management: an International Journal
Document relevance assessment via term distribution analysis using fourier series expansion
Proceedings of the 9th ACM/IEEE-CS joint conference on Digital libraries
Retrieval parameter optimization using genetic algorithms
Information Processing and Management: an International Journal
Improving MEDLINE document retrieval using automatic query expansion
ICADL'07 Proceedings of the 10th international conference on Asian digital libraries: looking back 10 years and forging new frontiers
Word distribution analysis for relevance ranking and query expansion
CICLing'08 Proceedings of the 9th international conference on Computational linguistics and intelligent text processing
On the query reformulation technique for effective MEDLINE document retrieval
Journal of Biomedical Informatics
Learning Aggregation Functions for Expert Search
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
A Data-Driven Approach to Measure Web Site Navigability
Journal of Management Information Systems
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Both ranking functions and user queries are very important factors affecting a search engine's performance. Prior research has looked at how to improve ad-hoc retrieval performance for existing queries while tuning the ranking function, or modify and expand user queries using a fixed ranking scheme using blind feedback. However, almost no research has looked at how to combine ranking function tuning and blind feedback together to improve ad-hoc retrieval performance. In this paper, we look at the performance improvement for ad-hoc retrieval from a more integrated point of view by combining the merits of both techniques. In particular, we argue that the ranking function should be tuned first, using user-provided queries, before applying the blind feedback technique. The intuition is that highly-tuned ranking offers more high quality documents at the top of the hit list, thus offers a stronger baseline for blind feedback. We verify this integrated model in a large scale heterogeneous collection and the experimental results show that combining ranking function tuning and blind feedback can improve search performance by almost 30% over the baseline Okapi system.