Add to ORKGWe evaluate the use of clickthrough information as implicit relevance feedback in sessions. We employ records of user interactions with a search system for pictures retrieval: issued queries, clicked images, and purchased content; we investigate whether and how much of the past search history should be used in a feedback loop. We also assess the benefit of using clicked data as positive tokens of relevance to the task of estimating the probability of an image to be purchased
The way a searcher interacts with query results can reveal a lot about what is being sought. Conside...
Rigorous analysis of user interest in web documents is essential for the development of recommender ...
wuerzburg.de Learning-to-rank methods automatically generate ranking functions which can be used for...
We evaluate the use of clickthrough information as implicit relevance feedback in sessions. We emplo...
Search sessions consist of a person presenting a query to a search engine, followed by that person e...
The interactions of users with search engines can be seen as implicit relevance feedback by the user...
Searchers can find the construction of query statements for submission to Information Retrieval (IR)...
In this thesis, we aim at improving the search result quality by utilizing the search intelligence (...
In this paper we report on the application of two contrasting types of relevance feedback for web re...
In this article we describe an evaluation of relevance feedback (RF) algorithms using searcher simul...
In this paper we report on a study of implicit feedback models for unobtrusively tracking the inform...
In this paper we examine the extent to which implicit feedback (where the system attempts to estimat...
Abstract. Our goal in this study was to explore the potentials of extracting features from eye-track...
In this paper we present five user experiments on incorporating behavioural information into the rel...
In this paper we explore the benefits of latent variable modelling of clickthrough data in the domai...
The way a searcher interacts with query results can reveal a lot about what is being sought. Conside...
Rigorous analysis of user interest in web documents is essential for the development of recommender ...
wuerzburg.de Learning-to-rank methods automatically generate ranking functions which can be used for...
We evaluate the use of clickthrough information as implicit relevance feedback in sessions. We emplo...
Search sessions consist of a person presenting a query to a search engine, followed by that person e...
The interactions of users with search engines can be seen as implicit relevance feedback by the user...
Searchers can find the construction of query statements for submission to Information Retrieval (IR)...
In this thesis, we aim at improving the search result quality by utilizing the search intelligence (...
In this paper we report on the application of two contrasting types of relevance feedback for web re...
In this article we describe an evaluation of relevance feedback (RF) algorithms using searcher simul...
In this paper we report on a study of implicit feedback models for unobtrusively tracking the inform...
In this paper we examine the extent to which implicit feedback (where the system attempts to estimat...
Abstract. Our goal in this study was to explore the potentials of extracting features from eye-track...
In this paper we present five user experiments on incorporating behavioural information into the rel...
In this paper we explore the benefits of latent variable modelling of clickthrough data in the domai...
The way a searcher interacts with query results can reveal a lot about what is being sought. Conside...
Rigorous analysis of user interest in web documents is essential for the development of recommender ...
wuerzburg.de Learning-to-rank methods automatically generate ranking functions which can be used for...