... utilizing relevance feed- back (RF) for time series, which has enjoyed a great deal of attention in information ...based relevancefeedback in our PVLDB paper ...
... Relevancefeedback works in the following way: a user submits a query representing his/her information need to the IR system, which then ranks the documents according to their corresponding degrees of ...
... A feature vector reduction described in Section 3 is embed- ded into our CBIR relevancefeedback module reported in [25, 26]. A system is tested by using images from unclassified TRECVid 2006 dataset and ...
... of RelevanceFeedback. Many schemes and techniques of relevancefeedback exist with many assumptions and operating ...implementing relevancefeedback in ...
... Future work will explore alternative methods for generating query terms including other types of relevancefeedback and lexical association mea- sures (e.g. Chi-squared and mutual information). Experiments ...
... All the publications that are retrieved from PubMed need to be transformed to a format that can be used by the system and its model. In the case of the re-ranking and relevancefeedback models, TFIDF and BM ...
... of RelevanceFeedback (RF) approaches have been widely developed to reduce this semantic gap which leads to much improved retrieval performance by updating a query and similarity measures according to users ...
... This study explored the effectiveness of a classical information retrieval (IR) approach, pseudo-relevancefeedback (PRF), on improving the performance of microblog search. Factors including number of PRF ...
... retrieval, RelevanceFeedback (RF) is an interactive process, which builds a bridge to connect users with a search ...the RelevanceFeedback mechanism. Based on this feedback the CBIR ...
... this relevancefeedback mechanism, the feature weights are updated at each iteration by calculating the precision and order of the rank of relevant images from retrieved images in individual ...
... (clusters), relevance (weights) of features and the number of times these images are selected as a query and marked as positive or ...probabilistic relevancefeedback method to improve the retrieval ...
... Implicit relevancefeedback has proved to be a important resource in improv- ing search accuracy and ...user relevancefeedback data, based on insights from query log ...ulated ...
... practice, relevancefeedback can be very effective but it relies on users assessing the relevance of documents and indicating to the system which documents contain relevant ...for relevance, ...
... Our approach is based on the advancement in language modeling approaches to information re- trieval (IR) (Croft and Lafferty, 2003) and extends these to incorporate CF. The motivation behind our approach is the analogy ...
... A relevancefeedback mechanism is also involved to tailor to individual’s memory strength and revisitation ...With relevancefeedback, the finding rate of WebPagePrevincreases by ...
... Although the pseudo RF techniques described in this section can improve retrieval performance over not using pseudo RF, the problem still remains that it is a variable technique: some queries will be improved, others ...
... xviii ABSTRACT Abstract This thesis is aimed at investigating interactive query expansion within the context of a relevance feedback system that uses term weighting and ranking in search[r] ...
... Relevancefeedback techniques are designed to automatically improve a system's representation of a query by using documents the user has marked as ...traditional relevancefeedback models ...
... Sanderson, M. and Clough, P. (2004) Relevancefeedback for cross language image retrieval. In: Advances in Information Retrieval : 26th European Conference on IR Research, ECIR 2004, Sunderland, UK, April ...
... SVM relevancefeedback technique on the Wang dataset is observed in terms of precision, recall, F-measure, and ...SVM relevancefeedback technique is also concerned with the selection of ...