OHSUMED: an interactive retrieval evaluation and new large test collection for research
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
On saying “Enough already!” in SQL
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
Optimal aggregation algorithms for middleware
PODS '01 Proceedings of the twentieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
PREFER: a system for the efficient execution of multi-parametric ranked queries
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Support vector machine active learning for image retrieval
MULTIMEDIA '01 Proceedings of the ninth ACM international conference on Multimedia
Minimal probing: supporting expensive predicates for top-k queries
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
Less is More: Active Learning with Support Vector Machines
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Incremental Support Vector Machine Construction
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Support Vector Machine Active Learning with Application sto Text Classification
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Reducing the Braking Distance of an SQL Query Engine
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Evaluating Top-k Selection Queries
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Optimizing search engines using clickthrough data
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Evaluating Top-k Queries over Web-Accessible Databases
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
An approach to incremental SVM learning algorithm
ICTAI '00 Proceedings of the 12th IEEE International Conference on Tools with Artificial Intelligence
Active learning of label ranking functions
ICML '04 Proceedings of the twenty-first international conference on Machine learning
RankFP: A Framework for Supporting Rank Formulation and Processing
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
RankSQL: query algebra and optimization for relational top-k queries
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Query chains: learning to rank from implicit feedback
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
SVM selective sampling for ranking with application to data retrieval
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Learning to rank using gradient descent
ICML '05 Proceedings of the 22nd international conference on Machine learning
Adapting ranking SVM to document retrieval
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Training linear SVMs in linear time
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Enabling soft queries for data retrieval
Information Systems
Ranking with multiple hyperplanes
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
AdaRank: a boosting algorithm for information retrieval
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
RankSVR: can preference data help regression?
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Exact indexing for support vector machines
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Noisy data elimination using mutual k-nearest neighbor for classification mining
Journal of Systems and Software
iKernel: Exact indexing for support vector machines
Information Sciences: an International Journal
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As many databases have been brought online, data retrieval--finding relevant data from large databases--has become a nontrivial task. A feedback-based data retrieval system was proposed to provide user with an intuitive way for expressing their preferences in queries. The system iteratively receives a partial ordering on a sample of data from the user, learns a ranking function, and returns highly ranked results according to the function. An important issue in such retrieval systems is minimizing the number of iterations or the amount of feedback to learn an accurate ranking function. This paper proposes selective sampling (or active learning) techniques for RankSVM that can be used in the retrieval systems. The proposed techniques minimizes the amount of user interaction to learn an accurate ranking function thus facilitates users formulating a preference query in the data retrieval system.