Implicit relevance feedback (IRF) is the process by which a search system unobtrusively gathers evidence on searcher interests from their interaction with the system. IRF is a new method of gathering information on user interest and, if IRF is to be used in operational IR systems, it is important to establish when it performs well and when it performs poorly. In this paper we investigate how the use and effectiveness of IRF is affected by three factors: search task complexity, the search experience of the user and the stage in the search. Our findings suggest that all three of these factors contribute to the utility of IRF
We evaluate the use of clickthrough information as implicit relevance feedback in sessions. We emplo...
AbstractRigorous analysis of user interest in web documents is essential for the development of reco...
Users of online web engines frequently think that it�s hard to express their requirement for informa...
Implicit relevance feedback (IRF) is the process by which a search system unobtrusively gathers evid...
Searchers can find the construction of query statements for submission to Information Retrieval (IR)...
In this paper we report on a study of implicit feedback models for unobtrusively tracking the inform...
In this article we describe an evaluation of relevance feedback (RF) algorithms using searcher simul...
In this paper we report on the application of two contrasting types of relevance feedback for web re...
In this paper we examine the extent to which implicit feedback (where the system attempts to estimat...
In this paper we present five user experiments on incorporating behavioural information into the rel...
Abstract. Our goal in this study was to explore the potentials of extracting features from eye-track...
Rigorous analysis of user interest in web documents is essential for the development of recommender ...
Users of online search engines often find it difficult to express their need for information in the ...
Rigorous analysis of user interest in web documents is essential for the development of recommender ...
Advances in search technology have meant that search systems can now offer assistance to users beyon...
We evaluate the use of clickthrough information as implicit relevance feedback in sessions. We emplo...
AbstractRigorous analysis of user interest in web documents is essential for the development of reco...
Users of online web engines frequently think that it�s hard to express their requirement for informa...
Implicit relevance feedback (IRF) is the process by which a search system unobtrusively gathers evid...
Searchers can find the construction of query statements for submission to Information Retrieval (IR)...
In this paper we report on a study of implicit feedback models for unobtrusively tracking the inform...
In this article we describe an evaluation of relevance feedback (RF) algorithms using searcher simul...
In this paper we report on the application of two contrasting types of relevance feedback for web re...
In this paper we examine the extent to which implicit feedback (where the system attempts to estimat...
In this paper we present five user experiments on incorporating behavioural information into the rel...
Abstract. Our goal in this study was to explore the potentials of extracting features from eye-track...
Rigorous analysis of user interest in web documents is essential for the development of recommender ...
Users of online search engines often find it difficult to express their need for information in the ...
Rigorous analysis of user interest in web documents is essential for the development of recommender ...
Advances in search technology have meant that search systems can now offer assistance to users beyon...
We evaluate the use of clickthrough information as implicit relevance feedback in sessions. We emplo...
AbstractRigorous analysis of user interest in web documents is essential for the development of reco...
Users of online web engines frequently think that it�s hard to express their requirement for informa...