The effect of accessing nonmatching documents on relevance feedback
ACM Transactions on Information Systems (TOIS)
Modern Information Retrieval
Data Mining: Concepts, Models, Methods and Algorithms
Data Mining: Concepts, Models, Methods and Algorithms
IDA '01 Proceedings of the 4th International Conference on Advances in Intelligent Data Analysis
Optimizing web search using web click-through data
Proceedings of the thirteenth ACM international conference on Information and knowledge management
Relevance feedback using weight propagation compared with information-theoretic query expansion
ECIR'07 Proceedings of the 29th European conference on IR research
Progress in information retrieval
ECIR'06 Proceedings of the 28th European conference on Advances in Information Retrieval
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A new Relevance Feedback (RF) technique is developed to improve upon the efficiency and performance of existing techniques. This is based on propagating positive and negative weights from documents judged relevant and not relevant respectively, to other documents, which are deemed similar according to one of a number of criteria. The performance and efficiency improve since the documents are treated as independent vectors rather than being merged into a single vector as is the case with traditional approaches, and only the documents considered in a given neighbourhood are inspected. This is especially important when using large test collections.