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Yang, J. (author), Hauff, C. (author), Bozzon, A. (author), Houben, G.J.P.M. (author)
Collaborative Question Answering (cQA) platforms are a very popular repository of crowd-generated knowledge. By formulating questions, users express needs that other members of the cQA community try to collaboratively satisfy. Poorly formulated questions are less likely to receive useful responses, thus hindering the overall knowledge generation...
conference paper 2014
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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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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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Sharifi Noorian, S. (author), Qiu, S. (author), Sayin, Burcu (author), Balayn, A.M.A. (author), Gadiraju, Ujwal (author), Yang, J. (author), Bozzon, A. (author)
High-quality data plays a vital role in developing reliable image classification models. Despite that, what makes an image difficult to classify remains an unstudied topic. This paper provides a first-of-its-kind, model-agnostic characterization of image atypicality based on human understanding. We consider the setting of image classification...
conference paper 2023
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Yang, J. (author), Bozzon, A. (author)
Micro-task crowdsourcing has become a successful mean to obtain high-quality data from a large crowd of diverse people. In this context, trust between all the involved actors (i.e. requesters, workers, and platform owners) is a critical factor for acceptance and long-term success. As actors have no expectation for “real life” meetings, thus...
conference paper 2016
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Yang, J. (author), Cantador, Iván (author), Nurbakova, Diana (author), Cortés-Cediel, María E. (author), Bozzon, A. (author)
This manifesto summarises the outcomes of the 1st Workshop on Recommender Systems for Citizens (CitRec'17), held at the 11th ACM Conference on Recommender Systems, in August 2017 in Como, Italy. We discuss challenges and opportunities for the development of recommender systems for citizens, including: the clarification of the role of recommender...
conference paper 2017
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Afentoulidis, G. (author), Szlávik, Z. (author), Yang, J. (author), Bozzon, A. (author)
Enterprise crowdsourcing capitalises on the availability of employees for in-house data processing. Gamification techniques can help aligning employees' motivation to the crowdsourcing endeavour. Although hitherto, research efforts were able to unravel the wide arsenal of gamification techniques to construct engagement loops, little research has...
conference paper 2018
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Sun, Zhu (author), Yang, J. (author), Zhang, Jie (author), Bozzon, A. (author), Chen, Yu (author), Xu, Chi (author)
Representation learning (RL) has recently proven to be effective in capturing local item relationships by modeling item co-occurrence in individual user's interaction record. However, the value of RL for recommendation has not reached the full potential due to two major drawbacks: 1) recommendation is modeled as a rating prediction problem...
conference paper 2017
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Yang, J. (author), Sun, Zhu (author), Bozzon, A. (author), Zhang, J. (author), Larson, M.A. (author)
The "International Workshop on Recommender Systems for Citizens" (CitRec) is focused on a novel type of recommender systems both in terms of ownership and purpose: recommender systems run by citizens and serving society as a whole.
conference paper 2017
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Sun, Zhu (author), Yang, J. (author), Zhang, J. (author), Bozzon, A. (author), Huang, Long Kai (author), Xu, Chi (author)
Knowledge graphs (KGs) have proven to be effective to improve recommendation. Existing methods mainly rely on hand-engineered features from KGs (e.g., meta paths), which requires domain knowledge. This paper presents RKGE, a KG embedding approach that automatically learns semantic representations of both entities and paths between entities...
conference paper 2018
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Sharifi Noorian, S. (author), Qiu, S. (author), Gadiraju, Ujwal (author), Yang, J. (author), Bozzon, A. (author)
Unknown unknowns represent a major challenge in reliable image recognition. Existing methods mainly focus on unknown unknowns identification, leveraging human intelligence to gather images that are potentially difficult for the machine. To drive a deeper understanding of unknown unknowns and more effective identification and treatment, this...
conference paper 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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Balayn, A.M.A. (author), Rikalo, N. (author), Yang, J. (author), Bozzon, A. (author)
Handling failures in computer vision systems that rely on deep learning models remains a challenge. While an increasing number of methods for bug identification and correction are proposed, little is known about how practitioners actually search for failures in these models. We perform an empirical study to understand the goals and needs of...
conference paper 2023
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Mesbah, Sepideh (author), Arous, Ines (author), Yang, J. (author), Bozzon, A. (author)
Evaluating design ideas is necessary to predict their success and assess their impact early on in the process. Existing methods rely either on metrics computed by systems that are effective but subject to errors and bias, or experts' ratings, which are accurate but expensive and long to collect. Crowdsourcing offers a compelling way to...
conference paper 2023
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Yang, J. (author), Bozzon, A. (author), Gadiraju, Ujwal (author), Lease, Matthew (author)
contribution to periodical 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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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), Yang, J. (author), Szlávik, Zoltán (author), Bozzon, A. (author)
The automatic detection of conflictual languages (harmful, aggressive, abusive, and offensive languages) is essential to provide a healthy conversation environment on the Web. To design and develop detection systems that are capable of achieving satisfactory performance, a thorough understanding of the nature and properties of the targeted type...
journal article 2021
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Psyllidis, A. (author), Yang, J. (author), Bozzon, A. (author)
Traditional methods for studying the activity dynamics of people and their social interactions in cities require time-consuming and resource-intensive observations and surveys. Dynamic online trails from geosocial networks (e.g. Twitter, Instagram, Flickr etc.) have been increasingly used as proxies for human activity, focusing on mobility...
journal article 2018
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Dhiratara, Arkka (author), Yang, J. (author), Bozzon, A. (author), Houben, G.J.P.M. (author)
Social media data are increasingly used as the source of research in a variety of domains. A typical example is urban analytics, which aims at solving urban problems by analyzing data from different sources including social media. The potential value of social media data in tourism studies, which is one of the key topics in urban research,...
journal article 2016
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