Searched for: author%3A%22Lofi%2C+C.%22
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Ghahremani, A. (author), Lofi, C. (author)
Reliable Cardiovascular Disease (CVD) classification performed by a smart system can assist medical doctors in recognizing heart illnesses in patients more efficiently and effectively. Electrocardiogram (ECG) signals are an important diagnostic tool as they are already available early in the patients’ health diagnosis process and contain...
journal article 2023
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Samiotis, I.P. (author), Qiu, S. (author), Lofi, C. (author), Yang, J. (author), Gadiraju, Ujwal (author), Bozzon, A. (author)
Music content annotation campaigns are common on paid crowdsourcing platforms. Crowd workers are expected to annotate complex music artifacts, a task often demanding specialized skills and expertise, thus selecting the right participants is crucial for campaign success. However, there is a general lack of deeper understanding of the distribution...
journal article 2022
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Chu, L. (author), Masiliunas, Dainius (author), Crivellari, Alessandro (author), Lofi, C. (author)
The outbreak of the coronavirus disease 19 (Covid-19) has posed a worldwide threat to human beings, economic activities, and society. Enforced lockdowns for limiting the spread of Covid-19 virus also substantially reduce air pollutant emissions from vehicle traffic, industrial plants, etc. The lockdown restrictions have brought beneficial...
poster 2022
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Balayn, A.M.A. (author), Rikalo, N. (author), Lofi, C. (author), Yang, J. (author), Bozzon, A. (author)
Deep learning models for image classification suffer from dangerous issues often discovered after deployment. The process of identifying bugs that cause these issues remains limited and understudied. Especially, explainability methods are often presented as obvious tools for bug identification. Yet, the current practice lacks an understanding...
conference paper 2022
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Chu, L. (author), Nelen, Jeroen (author), Höller, L. (author), Lasch, Hülya (author), Schubert, Dirk (author), Hein, C.M. (author), Lofi, C. (author)
Long-term exposure to ambient air pollution is one of the main public health concerns worldwide. Exposure to air pollution is highly related to a range of diseases including respiratory and cardiovascular diseases, such as lung cancers, asthma, diabetes, irregular heartbeat, stroke and obesity [1-3]. The outbreak of the pathogenic agent of...
poster 2022
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Samiotis, I.P. (author), Lofi, C. (author), Alaka, Shaad (author), Liem, C.C.S. (author), Bozzon, A. (author)
In this demo we present Scriptoria, an online crowdsourcing system to tackle the complex transcription process of classical orchestral scores. The system’s requirements are based on experts’ feedback from classical orchestra members. The architecture enables an end- to-end transcription process (from PDF to MEI) using a scalable microtask design...
conference paper 2022
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Balayn, A.M.A. (author), Lofi, C. (author), Houben, G.J.P.M. (author)
The increasing use of data-driven decision support systems in industry and governments is accompanied by the discovery of a plethora of bias and unfairness issues in the outputs of these systems. Multiple computer science communities, and especially machine learning, have started to tackle this problem, often developing algorithmic solutions to...
journal article 2021
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Samiotis, I.P. (author), Qiu, S. (author), Lofi, C. (author), Yang, J. (author), Gadiraju, Ujwal (author), Bozzon, A. (author)
Music content annotation campaigns are common on paid crowdsourcing platforms. Crowd workers are expected to annotate complicated music artefacts, which can demand certain skills and expertise. Traditional methods of participant selection are not designed to capture these kind of domain-specific skills and expertise, and often domain-specific...
journal article 2021
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Balayn, A.M.A. (author), SOILIS, P. (author), Lofi, C. (author), Yang, J. (author), Bozzon, A. (author)
Global interpretability is a vital requirement for image classification applications. Existing interpretability methods mainly explain a model behavior by identifying salient image patches, which require manual efforts from users to make sense of, and also do not typically support model validation with questions that investigate multiple...
conference paper 2021
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Samiotis, I.P. (author), Lofi, C. (author), Bozzon, A. (author)
Automated methods and human annotation are being extensively utilized to scale up modern classification systems. Processes though such as music transcription, oppose certain challenges due to the complexity of the domain and the expertise needed to read and process music scores. In this work, we examine how music transcription could benefit from...
conference paper 2021
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Harting, Tom (author), Mesbah, S. (author), Lofi, C. (author)
We introduce a Language-consistent multi-lingual Open Relation Extraction Model (LOREM) for finding relation tuples of any type between entities in unstructured texts. LOREM does not rely on language-specific knowledge or external NLP tools such as translators or PoS-taggers, and exploits information and structures that are consistent over...
conference paper 2020
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Samiotis, I.P. (author), Qiu, S. (author), Mauri, A. (author), Liem, C.C.S. (author), Lofi, C. (author), Bozzon, A. (author)
Human annotation is still an essential part of modern transcription workflows for digitizing music scores, either as a standalone approach where a single expert annotator transcribes a complete score, or for supporting an automated Optical Music Recognition (OMR) system. Research on human computation has shown the effectiveness of crowdsourcing...
conference paper 2020
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Mesbah, S. (author), Yang, J. (author), Sips, R.H.J. (author), Valle Torre, M. (author), Lofi, C. (author), Bozzon, A. (author), Houben, G.J.P.M. (author)
Social media provides a timely yet challenging data source for adverse drug reaction (ADR) detection. Existing dictionary-based, semi-supervised learning approaches are intrinsically limited by the coverage and maintainability of laymen health vocabularies. In this paper, we introduce a data augmentation approach that leverages variational...
conference paper 2019
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van den Bercken, Laurens (author), Sips, R.H.J. (author), Lofi, C. (author)
Health literacy, i.e. the ability to read and understand medical text, is a relevant component of public health. Unfortunately, many medical texts are hard to grasp by the general population as they are targeted at highly-skilled professionals and use complex language and domain-specific terms. Here, automatic text simplification making text...
conference paper 2019
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Vliegenthart, Daniel (author), Mesbah, S. (author), Lofi, C. (author), Aizawa, Akiko (author), Bozzon, A. (author)
Named Entity Recognition (NER) for rare long-tail entities as e.g., often found in domain-specific scientific publications is a challenging task, as typically the extensive training data and test data for fine-tuning NER algorithms is lacking. Recent approaches presented promising solutions relying on training NER algorithms in an iterative...
conference paper 2019
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Valle Torre, M. (author), Ye, Mengmeng (author), Lofi, C. (author)
Effectively modelling and querying experience items like movies, books, or games in databases is challenging because these items are better described by their resulting user experience or perceived properties than by factual attributes. However, such information is often subjective, disputed, or unclear. Thus, social judgments like comments,...
conference paper 2019
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Zhao, Y. (author), Robal, T. (author), Lofi, C. (author), Hauff, C. (author)
The use of mobile technology has become a part of our daily<br/>lives and enabled us to perform tasks that once were possible only on<br/>stationary computers on-the-go anywhere and at any time. This shift<br/>has also affected the way we learn. The use of mobile devices on-the-go<br/>requires users to multitask and divide attention between...
conference paper 2018
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Mesbah, S. (author), Bozzon, A. (author), Lofi, C. (author), Houben, G.J.P.M. (author)
This demo presents SmartPub, a novel web-based platform that supports the exploration and visualization of shallow meta-data (e.g., author list, keywords) and deep meta-data--long tail named entities which are rare, and often relevant only in specific knowledge domain--from scientific publications. The platform collects documents from different...
conference paper 2018
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Robal, T. (author), Zhao, Y. (author), Lofi, C. (author), Hauff, C. (author)
Massive Open Online Courses (MOOCs) have become an attractive opportunity for people around the world to gain knowledge and skills. Despite the initial enthusiasm of the first wave of MOOCs and the subsequent research efforts, MOOCs today suffer from retention issues: many MOOC learners start but do not finish. A main culprit is the lack of...
conference paper 2018
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Mesbah, S. (author), Lofi, C. (author), Valle Torre, M. (author), Bozzon, A. (author), Houben, G.J.P.M. (author)
Named Entity Recognition and Typing (NER/NET) is a challenging task, especially with long-tail entities such as the ones found in scientific publications. These entities (e.g. “WebKB”, “StatSnowball”) are rare, often relevant only in specific knowledge domains, yet important for retrieval and exploration purposes. State-of-the-art NER approaches...
conference paper 2018
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