Results 41 to 50 of about 5,543,464 (336)
Exploring EEG for Object Detection and Retrieval [PDF]
, 2015 This paper explores the potential for using Brain Computer Interfaces (BCI) as a relevance feedback mechanism in content-based image retrieval. We investigate if it is possible to capture useful EEG signals to detect if relevant objects are present in a ...
Giró-i-Nieto, Xavier +7 more
core +2 more sources
Denoising Implicit Feedback for Recommendation [PDF]
Web Search and Data Mining, 2020 The ubiquity of implicit feedback makes them the default choice to build online recommender systems. While the large volume of implicit feedback alleviates the data sparsity issue, the downside is that they are not as clean in reflecting the actual ...
Wenjie Wang +4 more
semanticscholar +1 more source
Using the Context of User Feedback in Recommender Systems [PDF]
Electronic Proceedings in Theoretical Computer Science, 2016 Our work is generally focused on recommending for small or medium-sized e-commerce portals, where explicit feedback is absent and thus the usage of implicit feedback is necessary. Nonetheless, for some implicit feedback features, the presentation context
Ladislav Peska
doaj +1 more source
Repeated training with augmentative vibrotactile feedback increases object manipulation performance. [PDF]
PLoS ONE, 2012 Most users of prosthetic hands must rely on visual feedback alone, which requires visual attention and cognitive resources. Providing haptic feedback of variables relevant to manipulation, such as contact force, may thus improve the usability of ...
Cara E Stepp, Qi An, Yoky Matsuoka
doaj +1 more source
Inferring Semantic Relations by User Feedback [PDF]
, 2014 In the last ten years, ontology-based recommender systems have been shown to be effective tools for predicting user preferences and suggesting items. There are however some issues associated with the ontologies adopted by these approaches, such as: 1) their crafting is not a cheap process, being time consuming and calling for specialist expertise; 2 ...
Francesco Osborne, Enrico Motta
openaire +2 more sources
End-user feedback in multi-user workflow systems [PDF]
Proceedings of the 32nd Symposium on Implementation and Application of Functional Languages, 2020 Workflow systems are more and more common due to the automation of business processes. The automation of business processes enables organizations to simplify their processes, improve services and contain costs. A problem with using workflow systems is that processes once known by heart, are now hidden from the user.
Nico Naus, Johan Jeuring
openaire +1 more source
Towards Teachable Reasoning Systems: Using a Dynamic Memory of User Feedback for Continual System Improvement [PDF]
Conference on Empirical Methods in Natural Language Processing, 2022 Our goal is a teachable reasoning system for question-answering (QA), where a user can interact with faithful answer explanations, and correct its errors so that the system improves over time.
Bhavana Dalvi +2 more
semanticscholar +1 more source
Re-Enrichment Learning: Metadata Saliency for the Evolutive Personalization of a Recommender System
Applied Sciences, 2021 Many studies have been conducted on recommender systems in both the academic and industrial fields, as they are currently broadly used in various digital platforms to make personalized suggestions. Despite the improvement in the accuracy of recommenders,
Yuseok Ban, Kyungjae Lee
doaj +1 more source
The role of automated feedback in training and retaining biological recorders for citizen science [PDF]
, 2016 The rapid rise of citizen science, with lay people forming often extensive biodiversity sensor networks, is seen as a solution to the mismatch between data demand and supply while simultaneously engaging citizens with environmental topics.
Adams +28 more
core +1 more source
Feedback Loop and Bias Amplification in Recommender Systems [PDF]
International Conference on Information and Knowledge Management, 2020 Recommendation algorithms are known to suffer from popularity bias; a few popular items are recommended frequently while the majority of other items are ignored.
M. Mansoury +4 more
semanticscholar +1 more source