International audienceSome methods have been developed for automatic effectiveness evaluation without relevance judgments. We propose to use those methods, and their combination based on a machine learning approach, for query performance prediction. Moreover, since predicting average precision as it is usually done in query performance prediction literature is sensitive to the reference system that is chosen, we focus on predicting the average of average precision values over several systems. Results of an extensive experimental evaluation on ten TREC collections show that our proposed methods outperform state-of-the-art query performance predictors
Query performance prediction methods are usually applied to estimate the retrieval effectiveness of ...
The query-performance prediction task has been described as estimating retrieval effectiveness in th...
Query performance prediction (QPP) has been studied extensively in the IR community over the last tw...
Some methods have been developed for automatic effectiveness evaluation without relevance judgments....
Numerous studies have examined the ability of query performance prediction methods to estimate a que...
International audienceQuery performance prediction (QPP) aims at automatically estimating the inform...
There has been much work on devising query-performance prediction approaches that estimate search ef...
Query performance predictors are commonly evaluated by reporting correlation coefficients to denote ...
The query performance prediction (QPP) task is to estimate the effectiveness of a search performed i...
The query-performance prediction (QPP) task is estimat-ing retrieval effectiveness with no relevance...
In this thesis we consider users' attempts to express their information needs through queries, or se...
Query performance predictors are commonly evaluated by reporting correlation coefficients to denote ...
In this paper, we examine a number of newly applied methods for combining pre-retrieval query perfor...
In this paper, we examine a number of newly applied methods for combining pre-retrieval query perfor...
Query performance prediction aims to predict whether a query will have a high average precision give...
Query performance prediction methods are usually applied to estimate the retrieval effectiveness of ...
The query-performance prediction task has been described as estimating retrieval effectiveness in th...
Query performance prediction (QPP) has been studied extensively in the IR community over the last tw...
Some methods have been developed for automatic effectiveness evaluation without relevance judgments....
Numerous studies have examined the ability of query performance prediction methods to estimate a que...
International audienceQuery performance prediction (QPP) aims at automatically estimating the inform...
There has been much work on devising query-performance prediction approaches that estimate search ef...
Query performance predictors are commonly evaluated by reporting correlation coefficients to denote ...
The query performance prediction (QPP) task is to estimate the effectiveness of a search performed i...
The query-performance prediction (QPP) task is estimat-ing retrieval effectiveness with no relevance...
In this thesis we consider users' attempts to express their information needs through queries, or se...
Query performance predictors are commonly evaluated by reporting correlation coefficients to denote ...
In this paper, we examine a number of newly applied methods for combining pre-retrieval query perfor...
In this paper, we examine a number of newly applied methods for combining pre-retrieval query perfor...
Query performance prediction aims to predict whether a query will have a high average precision give...
Query performance prediction methods are usually applied to estimate the retrieval effectiveness of ...
The query-performance prediction task has been described as estimating retrieval effectiveness in th...
Query performance prediction (QPP) has been studied extensively in the IR community over the last tw...