In the area of information retrieval the concept of relevance feedback is used to provide high relevant documents to the user. The process of gaining relevance data is usually based on explicit Relevance Feedback. But it turned out, that users are usually not willing to provide such data. This paper describes a Relevance Feedback approach that supports the users with query expansion terms by us...

Relevance feedback is an effective tool to bridge the gap between superficial image contents and medically-relevant sense in content-based medical image retrieval. In this paper, we propose an interactive medical image search framework based on pairwise constraint propagation. The basic idea is to obtain pairwise constraints from user feedback and propagate them to the entire image set to recon...

Existing document filtering systems learn user profiles based on user relevance feedback on documents. In some cases, users may have prior knowledge about what features are important. For example, a Spanish speaker may only want news written in Spanish, and thus a relevant document should contain the feature“Language: Spanish”; a researcher focusing on HIV knows an article with the medical subj...

The present study was conducted to further improve the practice of written corrective feedback by integrating the two known feedback types (i.e. direct corrective feedback and metalinguistic explanation). With this aim, a sample of sixty-nine high-intermediate Iranian EFL learners was assigned into different feedback groups. While the first and second groups received direct and metalinguistic e...

This study attempted to systematically inspect the impact of direct and indirect corrective feedbacks on the writing ability of EFL learners when using product/process based instructions. To do so, 110 female EFL learners, between the ages of 15 and 18, were randomly assigned into four experimental groups to receive four different kinds of treatments, namely product-based instruction with direc...

In this paper, we report our experiments in the TREC 2008 Relevance Feedback Track. Our main goal is to study a novel problem in feedback, i.e., optimization of the balance of the query and feedback information. Intuitively, if we over-trust the feedback information, we may be biased to favor a particular subset of relevant documents, but undertrusting it would not take advantage of feedback. I...

Augmented feedback, provided by coaches or displays, is a well-established strategy to accelerate motor learning. Frequent terminal feedback and concurrent feedback have been shown to be detrimental for simple motor task learning but supportive for complex motor task learning. However, conclusions on optimal feedback strategies have been mainly drawn from studies on artificial laboratory tasks ...

OBJECTIVES We examined whether feedback from an event-triggered video intervention system reduced the number of safety-relevant driving errors made by newly licensed adolescents. METHODS We used a 1-group pretest-posttest quasi-experimental design to compare the rate of coachable error events per 1000 miles for 18 drivers who were aged 16 years. The intervention consisted of immediate visual ...

OBJECTIVES Routine Outcome Monitoring (ROM) is an important quality tool for measuring outcome of treatment in health care. The objective of this article is to summarize the evidence base that supports the provision of feedback on ROM results to (mental) health care professionals and patients. Also, some relevant theoretical aspects are considered. METHODS Literature study (Pubmed, Medline, P...

We propose a new robust relevance model that can be applied to both pseudo feedback and true relevance feedback in the language-modeling framework for document retrieval. There are three main differences between our new relevance model and the Lavrenko-Croft relevance model. First, a query is treated as a short, special document and included in approximating a relevance model, in addition to a ...