Searched for: author:"Bozzon, A."
(1 - 20 of 36)

Pages

document
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
document
Sharifi Noorian, S. (author), Psyllidis, A. (author), Bozzon, A. (author)
Street-level imagery contains a variety of visual information about the facades of Points of Interest (POIs). In addition to general mor- phological features, signs on the facades of, primarily, business-related POIs could be a valuable source of information about the type and iden- tity of a POI. Recent advancements in computer vision could...
conference paper 2019
document
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
document
Mavridis, P. (author), Huang, Owen (author), Qiu, S. (author), Gadiraju, Ujwal (author), Bozzon, A. (author)
Conversational interfaces can facilitate human-computer interactions. Whether or not conversational interfaces can improve worker experience and work quality in crowdsourcing marketplaces has remained unanswered. We investigate the suitability of text-based conversational interfaces for microtask crowdsourcing. We designed a rigorous...
conference paper 2019
document
Harms, Jan-Gerrit (author), Kucherbaev, P. (author), Bozzon, A. (author), Houben, G.J.P.M. (author)
Dialog agents, like digital assistants and automated chat interfaces (e.g., chatbots), are becoming more and more popular as users adapt to conversing with their devices as they do with humans. In this paper, we present approaches and available tools for dialog management (DM), a component of dialog agents that handles dialog context and...
journal article 2019
document
Qiu, S. (author), Psyllidis, A. (author), Bozzon, A. (author), Houben, G.J.P.M. (author)
Knowledge about the organization of the main physical elements (e.g. streets) and objects (e.g. trees) that structure cities is important in the maintenance of city infrastructure and the planning of future urban interventions. In this paper, a novel approach to crowd-mapping urban objects is proposed. Our method capitalizes on strategies for...
conference paper 2019
document
Gong, X. (author), Daamen, W. (author), Bozzon, A. (author), Hoogendoorn, S.P. (author)
City events are being organized more frequently, and with larger crowds, in urban areas. There is an increased need for novel methods and tools that can provide information on the sentiments of crowds as an input for crowd management. Previous work has explored sentiment analysis and a large number of methods have been proposed relating to...
journal article 2019
document
de Kok, Roos (author), Mauri, A. (author), Bozzon, A. (author)
Understanding and improving the energy consumption behavior of individuals is considered a powerful approach to improve energy conservation and stimulate energy efficiency. To motivate people to change their energy consumption behavior, we need to have a thorough understanding of which energy-consuming activities they perform and how these...
journal article 2019
document
Kucherbaev, P. (author), Bozzon, A. (author), Houben, G.J.P.M. (author)
A chatbot is an example of a text-based conversational agent. While natural language understanding and machine learning techniques advance rapidly, current fully automated chatbots still struggle to serve their users well. Human intelligence, brought by crowd workers, freelancers or even full-time employees can be embodied in the chatbot logic...
journal article 2018
document
Gong, X. (author), Yang, J. (author), Daamen, W. (author), Bozzon, A. (author), Hoogendoorn, S.P. (author), Houben, G.J.P.M. (author)
City-scale events attract large amounts of attendees in temporarily re-purposed urban environments. In this setting, the real-time measurement of the density of attendees stationing in – or moving through – the event terrain is central to applications such as crowd management, emergency support, and quality of service...
journal article 2018
document
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
document
Sabou, Marta (author), Aroyo, Lora (author), Bontcheva, Kalina (author), Bozzon, A. (author), Qarout, Rehab K. (author)
contribution to periodical 2018
document
Bapat, Rucha (author), Kucherbaev, P. (author), Bozzon, A. (author)
Chatbots are text-based conversational agents. Natural Language Understanding (NLU) models are used to extract meaning and intention from user messages sent to chatbots. The user experience of chatbots largely depends on the performance of the NLU model, which itself largely depends on the initial dataset the model is trained with. The training...
conference paper 2018
document
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
document
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
document
Sharifi Noorian, S. (author), Psyllidis, A. (author), Bozzon, A. (author)
Location models have traditionally played an important role in suggesting sites for the placement of facilities, so that efficient service delivery is ensured. A common formulation of several location models is associated with the p-median problem, which aims to minimize the travel distance between support facilities and demand in a region....
conference paper 2018
document
Napoli, R. (author), Ertugrul, Ali Mert (author), Bozzon, A. (author), Brambilla, Marco (author)
This paper presents a user modeling pipeline to analyze discussions and opinions shared on social media regarding polarized political events (e.g., public polls). The pipeline follows a four-step methodology. First, social media posts and users metadata are crawled. Second, a filtering mechanism is applied to filter spammers and bot users. As a...
conference paper 2018
document
Balayn, A.M.A. (author), Mavridis, P. (author), Bozzon, A. (author), Timmermans, B.F.L. (author), Szlávik, Z. (author)
Training machine learning (ML) models for natural language processing usually requires large amount of data, often acquired through crowdsourcing. The way this data is collected and aggregated can have an effect on the outputs of the trained model such as ignoring the labels which differ from the majority. In this paper we investigate how label...
conference paper 2018
document
de Jong, M. (author), Mavridis, P. (author), Aroyo, Lora (author), Bozzon, A. (author), Vos, Jesse de (author), Oomen, Johan (author), Dimitrova, Antoaneta (author), Badenoch, Alec (author)
In this project we explore the presence of ambiguity in textual and visual media and its influence on accurately understanding and<br/>capturing bias in news. We study this topic in the context of supporting<br/>media scholars and social scientists in their media analysis. Our focus<br/>lies on racial and gender bias as well as framing and the...
conference paper 2018
document
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
Searched for: author:"Bozzon, A."
(1 - 20 of 36)

Pages