Predicting query performance, that is, the effectiveness of a search performed in response to a query, is a highly important and challenging problem.
We argue that query-drift can potentially be estimated by measuring the diversity (e.g., standard deviation) of the retrieval scores of these documents.
A Relative Information Gain-based Query Performance Prediction Framework with Generated Query Variants · Computer Science. ACM Trans. Inf. Syst. · 2023.
We develop a method for predicting query performance by computing the relative entropy between a query language model and the corresponding collection language ...
We present a novel approach to query-performance prediction that is based on estimating the potential amount of query drift in the result list — the documents.
Dec 31, 2011 · We present a novel approach to this task that is based on measuring the standard deviation of retrieval scores in the result list of the ...
We present a novel approach to query-performance prediction that is based on estimating the potential amount of query drift in the result list — the documents.
May 1, 2012 · Predicting query performance, that is, the effectiveness of a search performed in response to a query, is a highly important and challenging ...
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ABSTRACT. We investigate using topic prediction data, as a summary of document content, to compute measures of search result quality.
The goal of query performance prediction is to estimate a query's retrieval effectiveness without user feedback. Past research has investigated the usefulness ...