Towards interactive query expansion
SIGIR '88 Proceedings of the 11th annual international ACM SIGIR conference on Research and development in information retrieval
Information retrieval as statistical translation
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Exploiting a controlled vocabulary to improve collection selection and retrieval effectiveness
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Using terminological feedback for web search refinement: a log-based study
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Interactive Document Retrieval using Faceted Terminological Feedback
HICSS '99 Proceedings of the Thirty-Second Annual Hawaii International Conference on System Sciences-Volume 2 - Volume 2
Using bayesian priors to combine classifiers for adaptive filtering
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Active feedback in ad hoc information retrieval
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
The loquacious user: a document-independent source of terms for query expansion
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Elicitation of term relevance feedback: an investigation of term source and context
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Active Learning with Feedback on Features and Instances
The Journal of Machine Learning Research
Term feedback for information retrieval with language models
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NLP support for faceted navigation in scholarly collections
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Proceedings of the fourth ACM international conference on Web search and data mining
Filtering semi-structured documents based on faceted feedback
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Latent topic feedback for information retrieval
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Learning to rank with multi-aspect relevance for vertical search
Proceedings of the fifth ACM international conference on Web search and data mining
A comparative survey of Personalised Information Retrieval and Adaptive Hypermedia techniques
Information Processing and Management: an International Journal
A split-list approach for relevance feedback in information retrieval
Information Processing and Management: an International Journal
Summarizing highly structured documents for effective search interaction
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Multi-faceted ranking of news articles using post-read actions
Proceedings of the 21st ACM international conference on Information and knowledge management
Query recommendation for children
Proceedings of the 21st ACM international conference on Information and knowledge management
Journal of Web Engineering
Toward whole-session relevance: exploring intrinsic diversity in web search
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
Interactive exploratory search for multi page search results
Proceedings of the 22nd international conference on World Wide Web
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Motivated by the commonly used faceted search interface in e-commerce, this paper investigates interactive relevance feedback mechanism based on faceted document metadata. In this mechanism, the system recommends a group of document facet-value pairs, and lets users select relevant ones to restrict the returned documents. We propose four facet-value pair recommendation approaches and two retrieval models that incorporate user feedback on document facets. Evaluated based on user feedback collected through Amazon Mechanical Turk, our experimental results show that the Boolean filtering approach, which is widely used in faceted search in e-commerce, doesn't work well for text document retrieval, due to the incompleteness (low recall) of metadata assignment in semi-structured text documents. Instead, a soft model performs more effectively. The faceted feedback mechanism can also be combined with document-based relevance feedback and pseudo relevance feedback to further improve the retrieval performance.