Web search engines are one of the most popular tools on the Internet, which are widely used by experienced and inexperienced users. Constructing an adequate query, which represents the best specification of users’ information need to the search engine is an important concern of web users. Query expansion is a way to reduce this concern and increase user satisfaction. In this paper, a new method...

For the participation of Dublin City University (DCU) in the Relevance Feedback (RF) track of INEX 2010, we investigated the relation between the length of relevant text passages and the number of RF terms. In our experiments, relevant passages are segmented into non-overlapping windows of fixed length which are sorted by similarity with the query. In each retrieval iteration, we extend the cur...

Nowadays very large archives of digital images are easily produced thanks to the wide availability of digital cameras, that are often embedded into a number of portable devices. One of the ways of exploring an image archive is to search for similar images. Relevance feedback mechanisms can be employed to refine the search, as the most similar images according to a set of visual features may not...

Recently some CBIR approaches have shown the use of relevance feedback to train a pattern classifier to select relevant images for retrieval. This paper revisits this strategy by using an optimum-path forest (OPF) classifier. During relevance feedback iterations, the proposed method uses the OPF classifier to decide which database images are relevant or not. Images classified as relevant are so...

We describe the participation of the University of Amsterdam’s Intelligent Systems Lab in the relevance feedback track at TREC 2009. Our main conclusion for the relevance feedback track is that a topical diversity approach provides good feedback documents. Further, we find that our relevance feedback algorithm seems to help most when there are sufficient relevant documents available.

abstract the study aimed at investigating the efficacy of written corrective feedback (cf) in improving iranian efl learners’ grammatical accuracy. it compared the effects of focused and unfocused written cf on the learners’ grammatical accuracy. 75 efl students formed a one control and two experimental groups. the focused feedback group was provided with error correction in tenses. the unfocus...

High retrieval precision in content-based image retrieval can be attained by adopting relevance feedback mechanisms. These mechanisms require that the user judges the quality of the results of the query by marking all the retrieved images as being either relevant or not. Then, the search engine exploits this information to adapt the search to better meet user’s needs. At present, the vast major...

This document contains a description of experiments for the 2008 Relevance Feedback track. We experiment with different amounts of feedback, including negative relevance feedback. Feedback is implemented using massive weighted query expansion. Parsimonious query expansion using only relevant documents and Jelinek-Mercer smoothing performs best on this relevance feedback track dataset. Additiona...

In this paper we propose to incorporate a feedback loop, into the ordinal correlation framework and apply it to shapebased image retrieval. The user’s feedback on the relevance of the retrieval results is used to tune the weights of the similarity measure. Statistics from the features of both relevant and irrelevant items are used to estimate the weights. Moreover, the information accumulated f...

Feedback or closed-loop control allows dynamical systems to increase their performance up to a limit imposed by the second law of thermodynamics. It is expected that within this limit, the system performance increases as the controller uses more information about the system. However, despite the relevant progresses made recently, a general and complete formal development to justify this stateme...