Relevance feedback provides a measure of the extent to which the results of a search match the expectations of the user who initiated the query. Explicit feedback require users to assess relevance by choosing one out of a number of choices, or to rank documents to reflect their perceived degree of relevance. Implicit feedback is obtained by monitoring user’s behavior such as time spent browsing a document, amount of scrolling performed while browsing a document, number of times a document is visited, etc. Relevance feedback is one the techniques used to support query reformulation and turn the search into an iterative and interactive process.
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(2017). Relevance Feedback. In: Sammut, C., Webb, G.I. (eds) Encyclopedia of Machine Learning and Data Mining. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-7687-1_724
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DOI: https://doi.org/10.1007/978-1-4899-7687-1_724
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