The collection of user feedback as indications of users' interests resulted in a growing
interest in improving users' search experiences. In this article, we describe a method that …

Implicit feedback techniques appear to be attractive candidates to improve retrieval
performance through relevance feedback without requiring more effort on the part of the …

Implicit feedback algorithms utilize interaction between searchers and search systems to
learn more about users' needs and interests than expressed in query statements alone. This …

Purpose–The purpose of this paper is to improve users' search results relevancy by
manipulating their explicit feedback. Design/methodology/approach–CoRRe–an explicit …

Gathering evidence about whether a search result is relevant is a core concern in the
evaluation and improvement of information retrieval systems. Two common sources of …

Abstract Information Filtering systems learn user preferences either through explicit or
implicit feedback. However, requiring users to explicitly rate items as part of the interface …

Explicit relevance feedback involves explicit ratings of documents or terms by users and
disrupts their browsing and searching. The alternative non-disruptive method is implicit …

A user's goals and interests during an exploratory search task are often ambiguous and
complex. When engaging with new documents, people regularly use annotations to help …

Of growing interest in the area of improving the search experience is the collection of implicit
user behavior measures (implicit measures) as indications of user interest and user …

In real-life, information retrieval consists of sessions of one or more query iterations. Each
iteration has several subtasks like query formulation, result scanning, document link clicking …